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class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://unizg.academia.edu/AndrejDujella">Andrej Dujella</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">University of Zagreb</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a data-nosnippet="" href="https://ksu.academia.edu/DavidSeamon"><img class="profile-avatar u-positionAbsolute" alt="David Seamon related author profile picture" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/93547/25922/29662134/s200_david.seamon.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://ksu.academia.edu/DavidSeamon">David Seamon</a><p 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class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a data-nosnippet="" href="https://knust.academia.edu/WilliamObengDenteh"><img class="profile-avatar u-positionAbsolute" alt="William Obeng-Denteh related author profile picture" border="0" src="//a.academia-assets.com/images/s200_no_pic.png" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://knust.academia.edu/WilliamObengDenteh">William Obeng-Denteh</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">Kwame Nkrumah University of Science and Technology</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a data-nosnippet="" href="https://metode.academia.edu/JosepGuia"><img class="profile-avatar u-positionAbsolute" alt="Josep Guia related author profile picture" border="0" onerror="if (this.src != 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src="https://0.academia-photos.com/17255937/5084286/5829848/s200_adnan.awad.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://djasljsa.academia.edu/AdnanAwad">Adnan Awad</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">The University Of Jordan</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a data-nosnippet="" href="https://shams.academia.edu/MRaafat"><img class="profile-avatar u-positionAbsolute" alt="Mahmoud Raafat related author profile picture" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/18702462/5202094/5954101/s200_mahmoud.raafat.jpg_oh_444a0f1e56b8ee38c98f115b90bb8788_oe_54b3ef6f___gda___1421966701_496e89d5627cea3471875c2d2b8dd1a8" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://shams.academia.edu/MRaafat">Mahmoud Raafat</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">Ain Shams University</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a data-nosnippet="" href="https://yildiz.academia.edu/NasreenKausar"><img class="profile-avatar u-positionAbsolute" alt="Nasreen Kausar related author profile picture" border="0" onerror="if (this.src != '//a.academia-assets.com/images/s200_no_pic.png') this.src = '//a.academia-assets.com/images/s200_no_pic.png';" width="200" height="200" src="https://0.academia-photos.com/29298824/8376101/32886878/s200_nasreen.kausar.jpg" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://yildiz.academia.edu/NasreenKausar">Nasreen Kausar</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">Yildiz Technical University</p></div></div><div class="suggested-user-card"><div class="suggested-user-card__avatar social-profile-avatar-container"><a data-nosnippet="" href="https://bub.academia.edu/MedhaHuilgol"><img class="profile-avatar u-positionAbsolute" alt="Medha Huilgol related author profile picture" border="0" src="//a.academia-assets.com/images/s200_no_pic.png" /></a></div><div class="suggested-user-card__user-info"><a class="suggested-user-card__user-info__header ds2-5-body-sm-bold ds2-5-body-link" href="https://bub.academia.edu/MedhaHuilgol">Medha Huilgol</a><p class="suggested-user-card__user-info__subheader ds2-5-body-xs">Bangalore University</p></div></div></ul></div><style type="text/css">.suggested-academics--header h3{font-size:16px;font-weight:500;line-height:20px}</style><div class="ri-section"><div class="ri-section-header"><span>Interests</span></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="4524623" href="https://www.academia.edu/Documents/in/Bitopological_Spaces"><div id="js-react-on-rails-context" style="display:none" data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://sastra.academia.edu/KKANNAN","location":"/KKANNAN","scheme":"https","host":"sastra.academia.edu","port":null,"pathname":"/KKANNAN","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Bitopological Spaces"]}" data-trace="false" 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KANNAN</h3></div><div class="js-work-strip profile--work_container" data-work-id="115145853"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115145853/Soft_Generalized_Closed_Sets_in_Soft_Topological_Spaces"><img alt="Research paper thumbnail of Soft Generalized Closed Sets in Soft Topological Spaces" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title">Soft Generalized Closed Sets in Soft Topological Spaces</div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115145853"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115145853"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115145853; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115145853]").text(description); $(".js-view-count[data-work-id=115145853]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115145853; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115145853']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115145853]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115145853,"title":"Soft Generalized Closed Sets in Soft Topological Spaces","translated_title":"","metadata":{},"translated_abstract":null,"internal_url":"https://www.academia.edu/115145853/Soft_Generalized_Closed_Sets_in_Soft_Topological_Spaces","translated_internal_url":"","created_at":"2024-02-19T21:54:30.562-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":4524623,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Soft_Generalized_Closed_Sets_in_Soft_Topological_Spaces","translated_slug":"","page_count":null,"language":"en","content_type":"Work","summary":null,"owner":{"id":4524623,"first_name":"K.","middle_initials":null,"last_name":"KANNAN","page_name":"KKANNAN","domain_name":"sastra","created_at":"2013-06-12T19:45:45.890-07:00","display_name":"K. KANNAN","url":"https://sastra.academia.edu/KKANNAN"},"attachments":[],"research_interests":[{"id":300,"name":"Mathematics","url":"https://www.academia.edu/Documents/in/Mathematics"},{"id":143596,"name":"Soft Set","url":"https://www.academia.edu/Documents/in/Soft_Set"},{"id":782638,"name":"Topological Space","url":"https://www.academia.edu/Documents/in/Topological_Space"},{"id":2254216,"name":"Closed Set","url":"https://www.academia.edu/Documents/in/Closed_Set"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") if (false) { Aedu.setUpFigureCarousel('profile-work-115145853-figures'); } }); </script> <div class="js-work-strip profile--work_container" data-work-id="2941107"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/2941107/Some_types_of_separation_axioms_in_topological_spaces"><img alt="Research paper thumbnail of Some types of separation axioms in topological spaces " class="work-thumbnail" src="https://attachments.academia-assets.com/30899381/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/2941107/Some_types_of_separation_axioms_in_topological_spaces">Some types of separation axioms in topological spaces </a></div><div class="wp-workCard_item wp-workCard--coauthors"><span>by </span><span><a class="" data-click-track="profile-work-strip-authors" href="https://oud.academia.edu/AliasBKhalaf">Alias B. Khalaf</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://sastra.academia.edu/KKANNAN">K. KANNAN</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, co...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. The well-known Urysohn's Lemma and Tietze Extension Theorem are generalized to ω-normal spaces. We improve some known results. Also, some other concepts are generalized and studied via ω-open sets.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f925aee8cb14edd466204dec4c93cb00" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":30899381,"asset_id":2941107,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/30899381/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="2941107"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="2941107"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 2941107; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=2941107]").text(description); $(".js-view-count[data-work-id=2941107]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 2941107; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='2941107']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "f925aee8cb14edd466204dec4c93cb00" } } $('.js-work-strip[data-work-id=2941107]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":2941107,"title":"Some types of separation axioms in topological spaces ","translated_title":"","metadata":{"grobid_abstract":"In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. The well-known Urysohn's Lemma and Tietze Extension Theorem are generalized to ω-normal spaces. We improve some known results. 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KANNAN","title":"Some types of separation axioms in topological spaces "},{"id":20391848,"work_id":2941107,"tagging_user_id":817447,"tagged_user_id":40630373,"co_author_invite_id":null,"email":"s***h@yahoo.com","affiliation":"University of Sulaimani","display_order":6291456,"name":"halgwrd darwesh","title":"Some types of separation axioms in topological spaces "},{"id":20391849,"work_id":2941107,"tagging_user_id":817447,"tagged_user_id":12246470,"co_author_invite_id":null,"email":"k***h@gmail.com","display_order":7340032,"name":"Kamal AR","title":"Some types of separation axioms in topological spaces "}],"downloadable_attachments":[{"id":30899381,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/30899381/thumbnails/1.jpg","file_name":"Some_ypes_of_Separaion_Axioms.pdf","download_url":"https://www.academia.edu/attachments/30899381/download_file","bulk_download_file_name":"Some_types_of_separation_axioms_in_topol.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/30899381/Some_ypes_of_Separaion_Axioms-libre.pdf?1392063546=\u0026response-content-disposition=attachment%3B+filename%3DSome_types_of_separation_axioms_in_topol.pdf\u0026Expires=1743487789\u0026Signature=PgLhyeJoR9en27J5B2J7a~kGCLfDFhmfOAw94idA0TM7okiS-F3orsJieZyb9cW0lsHq8FKaU8NelpTnOXk509kXUfKr4h9CeMc8kOu56HOkh34Q98XSIyEiBdzMOoX8oMhclOxI0fNkppu4W7ixusjOB2rgaWlDKxVgcgRzZ0u-890KKqQfVo0cneZX3I5xkmSO78vFl3KN-8-uJUjgNnVbDlrupsafHQRyXEFlekBPnUTmaYVfIOY5yCXrM4SuV4Ci7QdJ6tV2mKDdycepnLRBxRqAB3mNZqiPbh6tDASCn~xbhVMa2l7YNficIawZGNM5fSiyYUkxWKEqZA2xJA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Some_types_of_separation_axioms_in_topological_spaces","translated_slug":"","page_count":24,"language":"en","content_type":"Work","summary":"In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. 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In particular it is proved that s * g -locally closed sets are closed under finite intersections. Also some implications of s * g -locally closed sets are given and we establish that some implications are not reversible, which are justified with suitable examples. Further some distinct notions of s * glc -continuity are introduced and we discuss some of their consequences like the composition of two s * glc -continuous functions and the restriction maps of s * glc -continuity.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="498e9ff77a58f4b46e6b2ec36a1c3051" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":33435398,"asset_id":6714569,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/33435398/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="6714569"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="6714569"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 6714569; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=6714569]").text(description); $(".js-view-count[data-work-id=6714569]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 6714569; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='6714569']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "498e9ff77a58f4b46e6b2ec36a1c3051" } } $('.js-work-strip[data-work-id=6714569]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":6714569,"title":"Some properties of s * g -locally closed sets","translated_title":"","metadata":{"grobid_abstract":"In this paper we continue the study of s * g -locally closed sets and s * gsubmaximal spaces in general topology. 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The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The quality of the performance is exhibited through the block diagram voice coder. In the last section, the tradeoffs between the bit rate for a plain LPC vocoder and the bit rate for a voice-excited LPC vocoder with DCT is analyzed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="fe6fc11ed322b8e5d3d8dd122ccfeca7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":33435390,"asset_id":6714567,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/33435390/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="6714567"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="6714567"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 6714567; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=6714567]").text(description); $(".js-view-count[data-work-id=6714567]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 6714567; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='6714567']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "fe6fc11ed322b8e5d3d8dd122ccfeca7" } } $('.js-work-strip[data-work-id=6714567]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":6714567,"title":"10 ICMS SPEECH PROCESSING LPC","translated_title":"","metadata":{"ai_title_tag":"Improved LPC for Tamil Speech Coding","grobid_abstract":"Wideband speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). 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In the last section, the tradeoffs between the bit rate for a plain LPC vocoder and the bit rate for a voice-excited LPC vocoder with DCT is analyzed.","grobid_abstract_attachment_id":33435390},"translated_abstract":null,"internal_url":"https://www.academia.edu/6714567/10_ICMS_SPEECH_PROCESSING_LPC","translated_internal_url":"","created_at":"2014-04-10T01:29:01.641-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":4524623,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":33435390,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/33435390/thumbnails/1.jpg","file_name":"10_ICMS_SPEECH_PROCESSING_LPC.pdf","download_url":"https://www.academia.edu/attachments/33435390/download_file","bulk_download_file_name":"10_ICMS_SPEECH_PROCESSING_LPC.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/33435390/10_ICMS_SPEECH_PROCESSING_LPC-libre.pdf?1397118376=\u0026response-content-disposition=attachment%3B+filename%3D10_ICMS_SPEECH_PROCESSING_LPC.pdf\u0026Expires=1743487789\u0026Signature=HxGWryULYD90wTRKdagxIiug6XPe~Bm0rHPXvNI2xQxI-~0QFPNgDZ7OlqcvSVENZjIPMdyOqCU51hLDbHFjYnIT4oqz8jluLbMVBUTNqUweExLPjNOc8v0HwzoIU~qW-YsUEiMPYAaJ1jQphb6LXH5xI19z2DsW7Behaq~fLVw40kcsP~5CF5FJ7X6kFB6ulEsZo6CBKR2GbzKleTwSemGRaVqRAHlv83UkAi-y-ezOe33pcCF-eQQ2HjqUX7u09SRcBVpKeQYF7uWA7aQQHXuArsfY4g0~xzTG3zCay3S8PanH1d8iSTsXiC8J5E6tjivXgCxhvZT3xJQrzfdfog__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"10_ICMS_SPEECH_PROCESSING_LPC","translated_slug":"","page_count":9,"language":"en","content_type":"Work","summary":"Wideband speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The quality of the performance is exhibited through the block diagram voice coder. In the last section, the tradeoffs between the bit rate for a plain LPC vocoder and the bit rate for a voice-excited LPC vocoder with DCT is analyzed.","owner":{"id":4524623,"first_name":"K.","middle_initials":null,"last_name":"KANNAN","page_name":"KKANNAN","domain_name":"sastra","created_at":"2013-06-12T19:45:45.890-07:00","display_name":"K. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") if (false) { Aedu.setUpFigureCarousel('profile-work-6714567-figures'); } }); </script> <div class="js-work-strip profile--work_container" data-work-id="6714566"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/6714566/09_IJCMS_S_STR_G_LOACLLY_CLOSED_SETS_BTS"><img alt="Research paper thumbnail of 09 IJCMS S STR G LOACLLY CLOSED SETS BTS" class="work-thumbnail" src="https://attachments.academia-assets.com/33435387/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/6714566/09_IJCMS_S_STR_G_LOACLLY_CLOSED_SETS_BTS">09 IJCMS S STR G LOACLLY CLOSED SETS BTS</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The aim of this paper is to introduce the concepts of semi star generalized locally closed sets, ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The aim of this paper is to introduce the concepts of semi star generalized locally closed sets, s * g submaximal spaces and study their basic properties in bitopological spaces.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="df00187c2084706b6c03ebe0c22a9c9f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":33435387,"asset_id":6714566,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/33435387/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="6714566"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="6714566"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 6714566; 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A sufficient condition for a soft g-closed set to be a soft closed is also presented. Moreover, the union and intersection of two soft g-closed sets are discussed. Finally, the new soft separation axiom, namely soft 1 2 T -space is introduced and its basic properties are investigated.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="486195c423c8a07537d364ae2486c408" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32406154,"asset_id":5220619,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32406154/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="5220619"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="5220619"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 5220619; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=5220619]").text(description); $(".js-view-count[data-work-id=5220619]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 5220619; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='5220619']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "486195c423c8a07537d364ae2486c408" } } $('.js-work-strip[data-work-id=5220619]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":5220619,"title":"Soft Generalized Closed Sets in Soft Topological Spaces","translated_title":"","metadata":{"grobid_abstract":"In the present paper, we introduce soft generalized closed sets in soft topological spaces which are defined over an initial universe with a fixed set of parameters. 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A sufficient condition for a soft g-closed set to be a soft closed is also presented. Moreover, the union and intersection of two soft g-closed sets are discussed. Finally, the new soft separation axiom, namely soft 1 2 T -space is introduced and its basic properties are investigated.","owner":{"id":4524623,"first_name":"K.","middle_initials":null,"last_name":"KANNAN","page_name":"KKANNAN","domain_name":"sastra","created_at":"2013-06-12T19:45:45.890-07:00","display_name":"K. 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The well-known Urysohn's Lemma and Tietze Extension Theorem are generalized to ω-normal spaces. We improve some known results. Also, some other concepts are generalized and studied via ω-open sets.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8692f0c02690f9a8ccb873d474383583" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32406113,"asset_id":3699596,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32406113/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="3699596"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="3699596"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3699596; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3699596]").text(description); $(".js-view-count[data-work-id=3699596]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3699596; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='3699596']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "8692f0c02690f9a8ccb873d474383583" } } $('.js-work-strip[data-work-id=3699596]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":3699596,"title":"Some Types of Separation Axioms in Topological Spaces","translated_title":"","metadata":{"ai_title_tag":"Separation Axioms via ω-open Sets in Topological Spaces","grobid_abstract":"In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. 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KANNAN","url":"https://sastra.academia.edu/KKANNAN"},"attachments":[{"id":32406113,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/32406113/thumbnails/1.jpg","file_name":"25_SOME_SEPARATION_AXIOMS_TAMSUI.pdf","download_url":"https://www.academia.edu/attachments/32406113/download_file","bulk_download_file_name":"Some_Types_of_Separation_Axioms_in_Topol.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/32406113/25_SOME_SEPARATION_AXIOMS_TAMSUI-libre.pdf?1391117535=\u0026response-content-disposition=attachment%3B+filename%3DSome_Types_of_Separation_Axioms_in_Topol.pdf\u0026Expires=1743487789\u0026Signature=dzRKmJKfeCIxNbEp8VhpcllOO4S8-pcB-612IPBwT9TPk9Y~cYX2MKJYH7pCrLceKZ8t7~O-9alZ79fbPnMSQP8U9BpSeVM7rDQVQRw5v~OpPlefnQnuyuxBE3UE6HqnnvKqAa~gOg2UHKGO1vnogdeedIxNFfgEmdl0od3IAlj4iCx706TGumguSrJ9RowW2LSPyMg7FpCfG7BQK8sVFoTIIJMHd72grvyZrqZa~Y6Qteh8sLoP6IdftYlwhB6ztQ6AFxWTMkpGEwzUZXP30l7MGdmxZsKiXatYEkOXMj40g3pwDsiLxjhRUNN3JAvPXsCYM0~pS67JyZ7GG287tQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[{"id":1991720,"url":"http://www1.au.edu.tw/ox_view/edu/tojms/j_paper/Full_text/Vol-28/No-3/28(3)8-7(303-326).pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") if (false) { Aedu.setUpFigureCarousel('profile-work-3699596-figures'); } }); </script> <div class="js-work-strip profile--work_container" data-work-id="3699520"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/3699520/Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM"><img alt="Research paper thumbnail of Speech Recognition of the letter 'zha' in Tamil Language using HMM" class="work-thumbnail" src="https://attachments.academia-assets.com/32406124/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/3699520/Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM">Speech Recognition of the letter 'zha' in Tamil Language using HMM</a></div><div class="wp-workCard_item"><span>Computing Research Repository</span><span>, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The output LPC cepstrum is implemented in first order three state Hidden Markov Model(HMM) chain.</span></div><div class="wp-workCard_item"><div class="carousel-container carousel-container--sm" id="profile-work-3699520-figures"><div class="prev-slide-container js-prev-button-container"><button aria-label="Previous" class="carousel-navigation-button js-profile-work-3699520-figures-prev"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">arrow_back_ios</span></button></div><div class="slides-container js-slides-container"><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242875/figure-1-speech-recognition-of-the-letter-zha-in-tamil"><img alt="" class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_001.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242879/figure-2-spectrogram-of-letter-zha-ip-experimental-results"><img alt="Figure 2: Spectrogram of letter ‘Zha’ (ip) . Experimental Results " class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_002.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242883/figure-3-sample-spectrum-section-plot-of-letter-zha-ip"><img alt="Sample spectrum section plot of letter “Zha’ (ip) 4.1, Spectrum plot " class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_003.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242887/figure-4-that-in-we-have-assumed-homogeneity-of-the-markov"><img alt="that in (1) we have assumed homogeneity of the Markov chain so that the transition probabilities do not depend on time. Assume that at t = 0 the state of the system qo is specified by an initial state probability 2;, = P (qo = i). Then, for any state sequence q = (qo, qi, q2,- - - , qr), the probability of q being generated by the Markov chain is " class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_004.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242893/figure-5-trellis-structure-for-the-calculation-of-the"><img alt="Figure 5. A Trellis Structure for the Calculation of the Forward Partial Probabilities @, (i). HMM method attractive and viable for speech recognizer designs because the evaluation problem can be viewed as one of scoring how well an unknown observation sequence (corresponding to the speech to be recognized) matches a given model (or sequence of models) source, thus providing an efficient mechanism for classification. 6.2 Estimation Problem Given an observation sequence (or a set of sequences) O, the estimation problem involves finding the "right" model parameter values that specify a model most likely to produce the given sequence. In speect recognition, this is often called "training," and the given sequence, on the basis of which we obtain the mode! parameters, is called the training sequence, even though the formulation here is statistical. In solving the estimation problem, the method of maximum likelihood (ML); that is, we choose 4 such that P (OA), as defined by (8), is maximized for the given training sequence O. 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The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The output LPC cepstrum is implemented in first order three state Hidden Markov Model(HMM) chain.","publication_date":{"day":null,"month":null,"year":2010,"errors":{}},"publication_name":"Computing Research Repository"},"translated_abstract":"Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The output LPC cepstrum is implemented in first order three state Hidden Markov Model(HMM) chain.","internal_url":"https://www.academia.edu/3699520/Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM","translated_internal_url":"","created_at":"2013-06-12T20:31:52.849-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":4524623,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":32406124,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/32406124/thumbnails/1.jpg","file_name":"11_IJEST_SPEECH_PROCESSING_HMM.pdf","download_url":"https://www.academia.edu/attachments/32406124/download_file","bulk_download_file_name":"Speech_Recognition_of_the_letter_zha_in.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/32406124/11_IJEST_SPEECH_PROCESSING_HMM-libre.pdf?1391589623=\u0026response-content-disposition=attachment%3B+filename%3DSpeech_Recognition_of_the_letter_zha_in.pdf\u0026Expires=1743487789\u0026Signature=KQRoMirvR4hpHQyYps2turyJQUB2W964ZEKMuxZnD2j8o9rPFgy1HsPpntG1gj7w6tiYa1xsu5cFv9VIp01cMvl1ZS9c87C4mEXW~5NF8IIk~ifCijpRoHjZB0GEGvL3m35Cv74EA1ev7lg7MX-oOA8Xm8~0-6j7Zyg9MQ2cDjxkbBblgUZ-kjeDGFNh92E0ZBN36U9KHSreOl~nxu4vRAg6Hu-5UIFlw8Wwnfjo2m77TZb-ioQNCOT9jaclCpGNcT5LXVY7W9qBMRG5aQcSoT97SxG7jrs5uoucdtxMq7YZF7ClhqYN2ryrBmiJB2~PYCLQbPhYJlBquJvIzDMkWA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM","translated_slug":"","page_count":6,"language":"en","content_type":"Work","summary":"Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). 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Chandrasekhara Rao and K. Joseph [5] introduced the concepts of semi star generalized open set...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">K. Chandrasekhara Rao and K. Joseph [5] introduced the concepts of semi star generalized open sets and semi star generalized closed sets in a topological space. The same concept was extended to bitopological spaces by K. Chandrasekhara Rao and K. Kannan . In this paper, we continue the study of τ 1 τ 2 -s * g closed sets in bitopology and we introduced the newly related concept of pairwise s * g-continuous mappings. Also S * GO-connectedness and S * GO-compactness are introduced in bitopological spaces and some of their properties are established.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ea5df6b1b36247290b9663dee1a075c5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32406130,"asset_id":3699368,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32406130/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="3699368"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="3699368"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3699368; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3699368]").text(description); $(".js-view-count[data-work-id=3699368]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3699368; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='3699368']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ea5df6b1b36247290b9663dee1a075c5" } } $('.js-work-strip[data-work-id=3699368]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":3699368,"title":"On semi star generalized closed sets in bitopological spaces","translated_title":"","metadata":{"grobid_abstract":"K. 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Chandrasekhara Rao and K. Joseph [5] introduced the concepts of semi star generalized open sets and semi star generalized closed sets in a topological space. The same concept was extended to bitopological spaces by K. Chandrasekhara Rao and K. Kannan . In this paper, we continue the study of τ 1 τ 2 -s * g closed sets in bitopology and we introduced the newly related concept of pairwise s * g-continuous mappings. Also S * GO-connectedness and S * GO-compactness are introduced in bitopological spaces and some of their properties are established.","owner":{"id":4524623,"first_name":"K.","middle_initials":null,"last_name":"KANNAN","page_name":"KKANNAN","domain_name":"sastra","created_at":"2013-06-12T19:45:45.890-07:00","display_name":"K. 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Khalaf</a> and <a class="" data-click-track="profile-work-strip-authors" href="https://sastra.academia.edu/KKANNAN">K. KANNAN</a></span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, co...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. The well-known Urysohn's Lemma and Tietze Extension Theorem are generalized to ω-normal spaces. We improve some known results. Also, some other concepts are generalized and studied via ω-open sets.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f925aee8cb14edd466204dec4c93cb00" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":30899381,"asset_id":2941107,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/30899381/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="2941107"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="2941107"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 2941107; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=2941107]").text(description); $(".js-view-count[data-work-id=2941107]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 2941107; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='2941107']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "f925aee8cb14edd466204dec4c93cb00" } } $('.js-work-strip[data-work-id=2941107]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":2941107,"title":"Some types of separation axioms in topological spaces ","translated_title":"","metadata":{"grobid_abstract":"In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. 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In particular it is proved that s * g -locally closed sets are closed under finite intersections. Also some implications of s * g -locally closed sets are given and we establish that some implications are not reversible, which are justified with suitable examples. Further some distinct notions of s * glc -continuity are introduced and we discuss some of their consequences like the composition of two s * glc -continuous functions and the restriction maps of s * glc -continuity.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="498e9ff77a58f4b46e6b2ec36a1c3051" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":33435398,"asset_id":6714569,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/33435398/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="6714569"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="6714569"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 6714569; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=6714569]").text(description); $(".js-view-count[data-work-id=6714569]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 6714569; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='6714569']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "498e9ff77a58f4b46e6b2ec36a1c3051" } } $('.js-work-strip[data-work-id=6714569]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":6714569,"title":"Some properties of s * g -locally closed sets","translated_title":"","metadata":{"grobid_abstract":"In this paper we continue the study of s * g -locally closed sets and s * gsubmaximal spaces in general topology. 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The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The quality of the performance is exhibited through the block diagram voice coder. In the last section, the tradeoffs between the bit rate for a plain LPC vocoder and the bit rate for a voice-excited LPC vocoder with DCT is analyzed.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="fe6fc11ed322b8e5d3d8dd122ccfeca7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":33435390,"asset_id":6714567,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/33435390/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="6714567"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="6714567"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 6714567; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=6714567]").text(description); $(".js-view-count[data-work-id=6714567]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 6714567; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='6714567']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "fe6fc11ed322b8e5d3d8dd122ccfeca7" } } $('.js-work-strip[data-work-id=6714567]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":6714567,"title":"10 ICMS SPEECH PROCESSING LPC","translated_title":"","metadata":{"ai_title_tag":"Improved LPC for Tamil Speech Coding","grobid_abstract":"Wideband speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). 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A sufficient condition for a soft g-closed set to be a soft closed is also presented. Moreover, the union and intersection of two soft g-closed sets are discussed. Finally, the new soft separation axiom, namely soft 1 2 T -space is introduced and its basic properties are investigated.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="486195c423c8a07537d364ae2486c408" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32406154,"asset_id":5220619,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32406154/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="5220619"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="5220619"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 5220619; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=5220619]").text(description); $(".js-view-count[data-work-id=5220619]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 5220619; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='5220619']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "486195c423c8a07537d364ae2486c408" } } $('.js-work-strip[data-work-id=5220619]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":5220619,"title":"Soft Generalized Closed Sets in Soft Topological Spaces","translated_title":"","metadata":{"grobid_abstract":"In the present paper, we introduce soft generalized closed sets in soft topological spaces which are defined over an initial universe with a fixed set of parameters. 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The well-known Urysohn's Lemma and Tietze Extension Theorem are generalized to ω-normal spaces. We improve some known results. Also, some other concepts are generalized and studied via ω-open sets.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="8692f0c02690f9a8ccb873d474383583" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32406113,"asset_id":3699596,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32406113/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="3699596"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="3699596"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3699596; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3699596]").text(description); $(".js-view-count[data-work-id=3699596]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3699596; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='3699596']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "8692f0c02690f9a8ccb873d474383583" } } $('.js-work-strip[data-work-id=3699596]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":3699596,"title":"Some Types of Separation Axioms in Topological Spaces","translated_title":"","metadata":{"ai_title_tag":"Separation Axioms via ω-open Sets in Topological Spaces","grobid_abstract":"In this paper, we introduce some types of separation axioms via ω-open sets, namely ω-regular, completely ω-regular and ω-normal space and investigate their fundamental properties, relationships and characterizations. 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KANNAN","url":"https://sastra.academia.edu/KKANNAN"},"attachments":[{"id":32406113,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/32406113/thumbnails/1.jpg","file_name":"25_SOME_SEPARATION_AXIOMS_TAMSUI.pdf","download_url":"https://www.academia.edu/attachments/32406113/download_file","bulk_download_file_name":"Some_Types_of_Separation_Axioms_in_Topol.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/32406113/25_SOME_SEPARATION_AXIOMS_TAMSUI-libre.pdf?1391117535=\u0026response-content-disposition=attachment%3B+filename%3DSome_Types_of_Separation_Axioms_in_Topol.pdf\u0026Expires=1743487789\u0026Signature=dzRKmJKfeCIxNbEp8VhpcllOO4S8-pcB-612IPBwT9TPk9Y~cYX2MKJYH7pCrLceKZ8t7~O-9alZ79fbPnMSQP8U9BpSeVM7rDQVQRw5v~OpPlefnQnuyuxBE3UE6HqnnvKqAa~gOg2UHKGO1vnogdeedIxNFfgEmdl0od3IAlj4iCx706TGumguSrJ9RowW2LSPyMg7FpCfG7BQK8sVFoTIIJMHd72grvyZrqZa~Y6Qteh8sLoP6IdftYlwhB6ztQ6AFxWTMkpGEwzUZXP30l7MGdmxZsKiXatYEkOXMj40g3pwDsiLxjhRUNN3JAvPXsCYM0~pS67JyZ7GG287tQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[{"id":1991720,"url":"http://www1.au.edu.tw/ox_view/edu/tojms/j_paper/Full_text/Vol-28/No-3/28(3)8-7(303-326).pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") if (false) { Aedu.setUpFigureCarousel('profile-work-3699596-figures'); } }); </script> <div class="js-work-strip profile--work_container" data-work-id="3699520"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/3699520/Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM"><img alt="Research paper thumbnail of Speech Recognition of the letter 'zha' in Tamil Language using HMM" class="work-thumbnail" src="https://attachments.academia-assets.com/32406124/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/3699520/Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM">Speech Recognition of the letter 'zha' in Tamil Language using HMM</a></div><div class="wp-workCard_item"><span>Computing Research Repository</span><span>, 2010</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The output LPC cepstrum is implemented in first order three state Hidden Markov Model(HMM) chain.</span></div><div class="wp-workCard_item"><div class="carousel-container carousel-container--sm" id="profile-work-3699520-figures"><div class="prev-slide-container js-prev-button-container"><button aria-label="Previous" class="carousel-navigation-button js-profile-work-3699520-figures-prev"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">arrow_back_ios</span></button></div><div class="slides-container js-slides-container"><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242875/figure-1-speech-recognition-of-the-letter-zha-in-tamil"><img alt="" class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_001.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242879/figure-2-spectrogram-of-letter-zha-ip-experimental-results"><img alt="Figure 2: Spectrogram of letter ‘Zha’ (ip) . Experimental Results " class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_002.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242883/figure-3-sample-spectrum-section-plot-of-letter-zha-ip"><img alt="Sample spectrum section plot of letter “Zha’ (ip) 4.1, Spectrum plot " class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_003.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242887/figure-4-that-in-we-have-assumed-homogeneity-of-the-markov"><img alt="that in (1) we have assumed homogeneity of the Markov chain so that the transition probabilities do not depend on time. Assume that at t = 0 the state of the system qo is specified by an initial state probability 2;, = P (qo = i). Then, for any state sequence q = (qo, qi, q2,- - - , qr), the probability of q being generated by the Markov chain is " class="figure-slide-image" src="https://figures.academia-assets.com/32406124/figure_004.jpg" /></a></figure><figure class="figure-slide-container"><a href="https://www.academia.edu/figures/35242893/figure-5-trellis-structure-for-the-calculation-of-the"><img alt="Figure 5. A Trellis Structure for the Calculation of the Forward Partial Probabilities @, (i). HMM method attractive and viable for speech recognizer designs because the evaluation problem can be viewed as one of scoring how well an unknown observation sequence (corresponding to the speech to be recognized) matches a given model (or sequence of models) source, thus providing an efficient mechanism for classification. 6.2 Estimation Problem Given an observation sequence (or a set of sequences) O, the estimation problem involves finding the "right" model parameter values that specify a model most likely to produce the given sequence. In speect recognition, this is often called "training," and the given sequence, on the basis of which we obtain the mode! parameters, is called the training sequence, even though the formulation here is statistical. In solving the estimation problem, the method of maximum likelihood (ML); that is, we choose 4 such that P (OA), as defined by (8), is maximized for the given training sequence O. 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The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The output LPC cepstrum is implemented in first order three state Hidden Markov Model(HMM) chain.","publication_date":{"day":null,"month":null,"year":2010,"errors":{}},"publication_name":"Computing Research Repository"},"translated_abstract":"Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). The sampling frequency was at 16 kHz and the bit rate was at 15450 bits per second, where the original bit rate was at 128000 bits per second with the help of wave surfer audio tool. The output LPC cepstrum is implemented in first order three state Hidden Markov Model(HMM) chain.","internal_url":"https://www.academia.edu/3699520/Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM","translated_internal_url":"","created_at":"2013-06-12T20:31:52.849-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":4524623,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":32406124,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/32406124/thumbnails/1.jpg","file_name":"11_IJEST_SPEECH_PROCESSING_HMM.pdf","download_url":"https://www.academia.edu/attachments/32406124/download_file","bulk_download_file_name":"Speech_Recognition_of_the_letter_zha_in.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/32406124/11_IJEST_SPEECH_PROCESSING_HMM-libre.pdf?1391589623=\u0026response-content-disposition=attachment%3B+filename%3DSpeech_Recognition_of_the_letter_zha_in.pdf\u0026Expires=1743487789\u0026Signature=KQRoMirvR4hpHQyYps2turyJQUB2W964ZEKMuxZnD2j8o9rPFgy1HsPpntG1gj7w6tiYa1xsu5cFv9VIp01cMvl1ZS9c87C4mEXW~5NF8IIk~ifCijpRoHjZB0GEGvL3m35Cv74EA1ev7lg7MX-oOA8Xm8~0-6j7Zyg9MQ2cDjxkbBblgUZ-kjeDGFNh92E0ZBN36U9KHSreOl~nxu4vRAg6Hu-5UIFlw8Wwnfjo2m77TZb-ioQNCOT9jaclCpGNcT5LXVY7W9qBMRG5aQcSoT97SxG7jrs5uoucdtxMq7YZF7ClhqYN2ryrBmiJB2~PYCLQbPhYJlBquJvIzDMkWA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Speech_Recognition_of_the_letter_zha_in_Tamil_Language_using_HMM","translated_slug":"","page_count":6,"language":"en","content_type":"Work","summary":"Speech signals of the letter 'zha' in Tamil language of 3 males and 3 females were coded using an improved version of Linear Predictive Coding (LPC). 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Chandrasekhara Rao and K. Joseph [5] introduced the concepts of semi star generalized open set...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">K. Chandrasekhara Rao and K. Joseph [5] introduced the concepts of semi star generalized open sets and semi star generalized closed sets in a topological space. The same concept was extended to bitopological spaces by K. Chandrasekhara Rao and K. Kannan . In this paper, we continue the study of τ 1 τ 2 -s * g closed sets in bitopology and we introduced the newly related concept of pairwise s * g-continuous mappings. Also S * GO-connectedness and S * GO-compactness are introduced in bitopological spaces and some of their properties are established.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="ea5df6b1b36247290b9663dee1a075c5" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":32406130,"asset_id":3699368,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/32406130/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="3699368"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="3699368"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 3699368; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=3699368]").text(description); $(".js-view-count[data-work-id=3699368]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 3699368; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='3699368']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "ea5df6b1b36247290b9663dee1a075c5" } } $('.js-work-strip[data-work-id=3699368]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":3699368,"title":"On semi star generalized closed sets in bitopological spaces","translated_title":"","metadata":{"grobid_abstract":"K. 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Chandrasekhara Rao and K. Joseph [5] introduced the concepts of semi star generalized open sets and semi star generalized closed sets in a topological space. The same concept was extended to bitopological spaces by K. Chandrasekhara Rao and K. Kannan . In this paper, we continue the study of τ 1 τ 2 -s * g closed sets in bitopology and we introduced the newly related concept of pairwise s * g-continuous mappings. Also S * GO-connectedness and S * GO-compactness are introduced in bitopological spaces and some of their properties are established.","owner":{"id":4524623,"first_name":"K.","middle_initials":null,"last_name":"KANNAN","page_name":"KKANNAN","domain_name":"sastra","created_at":"2013-06-12T19:45:45.890-07:00","display_name":"K. 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