SpecGAN Explained | Papers With Code

<!doctype html> <html lang="en"> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"> <script> const GTAG_ENABLED = true ; const GTAG_TRACKING_ID = "UA-121182717-1"; const SENTRY_DSN_FRONTEND = "".trim(); const GLOBAL_CSRF_TOKEN = 'kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc'; const MEDIA_URL = "https://production-media.paperswithcode.com/"; const ASSETS_URL = "https://production-assets.paperswithcode.com"; run_after_frontend_loaded = window.run_after_frontend_loaded || []; </script> <link rel="preconnect" href="https://production-assets.paperswithcode.com"><link rel="dns-prefetch" href="https://production-assets.paperswithcode.com"><link rel="preload" as="font" type="font/woff2" href="https://production-assets.paperswithcode.com/perf/fonts/65e877e527022735c1a1.woff2" crossorigin><link rel="preload" as="font" type="font/woff2" href="https://production-assets.paperswithcode.com/perf/fonts/917632e36982ca7933c8.woff2" crossorigin><link rel="preload" as="font" type="font/woff2" href="https://production-assets.paperswithcode.com/perf/fonts/f1405bd8a987c2ea8a67.woff2" crossorigin><script>(()=>{if(GTAG_ENABLED){const t=document.createElement("script");function n(){window.dataLayer.push(arguments)}t.src=`https://www.googletagmanager.com/gtag/js?id=${GTAG_TRACKING_ID}`,document.head.appendChild(t),window.dataLayer=window.dataLayer||[],window.gtag=n,n("js",new Date),n("config",GTAG_TRACKING_ID),window.captureOutboundLink=function(t){n("event","click",{event_category:"outbound",event_label:t})}}else window.captureOutboundLink=function(n){document.location=n}})();</script><link rel="preload" as="script" href="https://production-assets.paperswithcode.com/perf/766.4af6b88b.js"><link rel="preload" as="script" href="https://production-assets.paperswithcode.com/perf/351.a22a9607.js"><link rel="preload" as="script" href="https://production-assets.paperswithcode.com/perf/814.49dcf06c.js"><link rel="preload" as="style" href="https://production-assets.paperswithcode.com/perf/918.c41196c3.css"><link rel="preload" as="style" href="https://production-assets.paperswithcode.com/perf/view_method.e499b4af.css"><link rel="preload" as="script" href="https://production-assets.paperswithcode.com/perf/view_method.c1f0a493.js"><link rel="stylesheet" href="https://production-assets.paperswithcode.com/perf/918.c41196c3.css"><link rel="stylesheet" href="https://production-assets.paperswithcode.com/perf/view_method.e499b4af.css">  <title>SpecGAN Explained | Papers With Code</title> <meta name="description" content="SpecGAN is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\left[−1, 1\right]$. They then use the DCGAN approach on the result spectra." />  <meta property="og:title" content="Papers with Code - SpecGAN Explained"> <meta property="og:description" content="SpecGAN is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\left[−1, 1\right]$. They then use the DCGAN approach on the result spectra."> <meta property="og:image" content="https://production-media.paperswithcode.com/methods/Screen_Shot_2020-07-05_at_5.41.33_PM_4WCRYJM.png"> <meta property="og:url" content="https://paperswithcode.com/method/specgan">  <meta name="twitter:card" content="summary_large_image"> <meta name="twitter:site" content="@paperswithcode"> <meta name="twitter:title" content="Papers with Code - SpecGAN Explained"> <meta name="twitter:description" content="SpecGAN is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\left[−1, 1\right]$. They then use the DCGAN approach on the result spectra."> <meta name="twitter:creator" content="@paperswithcode"> <meta name="twitter:url" content="https://paperswithcode.com/method/specgan"> <meta name="twitter:domain" content="paperswithcode.com">  <script type="application/ld+json">{ "@context": "http://schema.org", "@graph": { "@type": "CreativeWork", "@id": "specgan", "name": "SpecGAN Explained", "description": "SpecGAN is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. \n\nTo process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\\left[\u22121, 1\\right]$.\n\nThey then use the DCGAN approach on the result spectra.", "url": "https://paperswithcode.com/method/specgan", "image": "https://production-media.paperswithcode.com/methods/Screen_Shot_2020-07-05_at_5.41.33_PM_4WCRYJM.png", "headline": "SpecGAN Explained" } }</script> <meta name="theme-color" content="#fff"/> <link rel="manifest" href="https://production-assets.paperswithcode.com/static/manifest.web.json"> </head> <body> <nav class="navbar navbar-expand-lg navbar-light header"> <a class="navbar-brand" href="/"> <span class=" icon-wrapper" data-name="pwc"><svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path d="M88 128h48v256H88zm144 0h48v256h-48zm-72 16h48v224h-48zm144 0h48v224h-48zm72-16h48v256h-48z"/><path d="M104 104V56H16v400h88v-48H64V104zm304-48v48h40v304h-40v48h88V56z"/></svg></span> </a> <div class="navbar-mobile-twitter d-lg-none"> <a rel="noreferrer" 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method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\left[−1, 1\right]$. They then use the [DCGAN](https://paperswithcode.com/method/dcgan) approach on the result spectra.</textarea> </div> </div> <div id="div_id_code_snippet_url" class="form-group"> <label for="id_code_snippet_url" class=""> Code Snippet URL (optional): </label> <div class=""> <input type="text" name="code_snippet_url" maxlength="200" class="textinput textInput form-control" id="id_code_snippet_url"> </div> </div> <div id="div_id_image" class="form-group"> <label for="id_image" class=""> Image </label> <div class=""> Currently: <a href="https://production-media.paperswithcode.com/methods/Screen_Shot_2020-07-05_at_5.41.33_PM_4WCRYJM.png">methods/Screen_Shot_2020-07-05_at_5.41.33_PM_4WCRYJM.png</a> <input type="checkbox" name="image-clear" id="image-clear_id"> <label for="image-clear_id">Clear</label><br> Change: <input type="file" name="image" accept="image/*" class="clearablefileinput form-control-file" id="id_image"> </div> </div> <div class="modal-footer"> <button type="submit" 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aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <div class="modal-body"> <div class="current-tasks-title">Attached components:</div> <ul class="list-unstyled"> <li> <a href="/method/dcgan"> <span class="badge badge-primary">DCGAN</span> </a> </li> </ul> <ul class="list-unstyled"> <li> <a href="/method/griffin-lim-algorithm"> <span class="badge badge-primary">GRIFFIN-LIM ALGORITHM</span> </a> </li> </ul> <ul class="list-unstyled"> <li> <a href="/method/phase-shuffle"> <span class="badge badge-primary">PHASE SHUFFLE</span> </a> </li> </ul> <ul class="list-unstyled"> <li> <a href="/method/tanh-activation"> <span class="badge badge-primary">TANH ACTIVATION</span> </a> </li> </ul> <ul class="list-unstyled"> <li> <a href="/method/wgan-gp-loss"> <span class="badge badge-primary">WGAN-GP LOSS</span> </a> </li> </ul> <form action="" method="post"> <input type="hidden" name="csrfmiddlewaretoken" value="kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc"> <div 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class="modal-dialog" role="document"> <div class="modal-content"> <div class="modal-header"> <h5 class="modal-title" id="removeCompoenntnLabel">Remove a method component</h5> <button type="button" class="close btn-close" data-bs-dismiss="modal" aria-label="Close"> <span aria-hidden="true">×</span> </button> </div> <form action="" method="post"> <div class="modal-body"> <ul class="list-unstyled"> <form action="" method="post"> <li> <a href="/method/dcgan"> <span class="badge badge-primary">DCGAN</span> </a> <input type="hidden" name="csrfmiddlewaretoken" value="kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc"> <input type="hidden" name="remove_component_pk" value="470"> <button type="submit" class="btn btn-danger" style="width:2.5em">- </button> </li> </form> </ul> <ul class="list-unstyled"> <form action="" method="post"> <li> <a href="/method/griffin-lim-algorithm"> <span class="badge badge-primary">GRIFFIN-LIM ALGORITHM</span> </a> <input type="hidden" name="csrfmiddlewaretoken" value="kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc"> <input type="hidden" name="remove_component_pk" value="35"> <button type="submit" class="btn btn-danger" style="width:2.5em">- </button> </li> </form> </ul> <ul class="list-unstyled"> <form action="" method="post"> <li> <a href="/method/phase-shuffle"> <span class="badge badge-primary">PHASE SHUFFLE</span> </a> <input type="hidden" name="csrfmiddlewaretoken" value="kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc"> <input type="hidden" name="remove_component_pk" value="7"> <button type="submit" class="btn btn-danger" style="width:2.5em">- </button> </li> </form> </ul> <ul class="list-unstyled"> <form action="" method="post"> <li> <a href="/method/tanh-activation"> <span class="badge badge-primary">TANH ACTIVATION</span> </a> <input type="hidden" name="csrfmiddlewaretoken" value="kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc"> <input type="hidden" name="remove_component_pk" value="494"> <button type="submit" class="btn btn-danger" style="width:2.5em">- </button> </li> </form> </ul> <ul class="list-unstyled"> <form action="" method="post"> <li> <a href="/method/wgan-gp-loss"> <span class="badge badge-primary">WGAN-GP LOSS</span> </a> <input type="hidden" name="csrfmiddlewaretoken" value="kYdDaUnmG6OMUOsSEr8ubUufqjWBV6xvYGUK9UZSVLYmAnhofOLmkiHn6i4MH3Cc"> <input type="hidden" name="remove_component_pk" value="14"> <button type="submit" class="btn btn-danger" style="width:2.5em">- </button> </li> </form> </ul> </div> </form> </div> </div> </div> <div class="container content content-buffer "> <div class="mobile-width"> <div class="method-header"> <a href="/methods/category/generative-audio-models"> <span class="badge badge-primary"> <img src="https://production-media.paperswithcode.com/tasks/default.gif"> <span>Generative Audio Models</span> </span> </a> <div class="method-title"> <div class="row"> <div class="col-md-11"> <h1>SpecGAN</h1> <span class="method-subtitle">Introduced by Donahue et al. in <a href="/paper/adversarial-audio-synthesis">Adversarial Audio Synthesis</a></span> </div> <div class="col-md-1"> <div class="float-right"> <div class="dropdown edit-button"> <a data-bs-toggle="modal" data-bs-target="#loginModal"> <span class="badge badge-method-edit" style="padding-top:10px;"><span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit</span> </a> </div> </div> </div> </div> </div> <div class="method-content" style="margin-top: 2rem;"> <div class="row"> <div class="col-md-8 description"> <p><strong>SpecGAN</strong> is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted. </p> <p>To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to $\left[−1, 1\right]$.</p> <p>They then use the <a href="https://paperswithcode.com/method/dcgan">DCGAN</a> approach on the result spectra.</p> <span class="description-source"> Source: <a href="http://arxiv.org/abs/1802.04208v3"><span class=" icon-wrapper icon-ion" data-name="document-outline"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path d="M416 221.25V416a48 48 0 0 1-48 48H144a48 48 0 0 1-48-48V96a48 48 0 0 1 48-48h98.75a32 32 0 0 1 22.62 9.37l141.26 141.26a32 32 0 0 1 9.37 22.62z" fill="none" stroke="#000" stroke-linejoin="round" stroke-width="32"/><path d="M256 56v120a32 32 0 0 0 32 32h120" fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32"/></svg></span> Adversarial Audio Synthesis</a> </span> <div class="context"> <div class="row"> <div class="col-md-12"> <a href="https://arxiv.org/abs/1802.04208v3" onclick="captureOutboundLink('https://arxiv.org/abs/1802.04208v3'); return true;" class="badge badge-light"> Read Paper </a> <a href="/paper/adversarial-audio-synthesis#code" class="badge badge-light"> See Code </a> </div> </div> </div> </div> <div class="col-md-4"> <a href="#" id="pop"> <a href="https://production-media.paperswithcode.com/methods/Screen_Shot_2020-07-05_at_5.41.33_PM_4WCRYJM.png" data-lightbox="imageresource"> <img id="imageresource" width=100% src="https://production-media.paperswithcode.com/methods/Screen_Shot_2020-07-05_at_5.41.33_PM_4WCRYJM.png"> </a> </a> <div class="modal fade" id="imagemodal" tabindex="-1" role="dialog" aria-labelledby="imagePreview" aria-hidden="true"> <div class="modal-dialog modal-lg"> <div class="modal-content"> <div class="modal-body text-center"> <img class="method-image" src="" id="imagepreview" style="max-width: 750px;"> </div> </div> </div> </div> </div> </div> <div id="papers"> <h4 style="margin-bottom: 0.5rem">Papers</h4> <hr> <div class="sota-table-preview papers-datatable-component"> <table style="width: 100% !important;" id="datatable-papers" class="table-striped table-responsive"> <thead style="width: 100% !important;"> <tr> <th style="text-left"><span>Paper</span></th> <th class="text-center"><span>Code</span></th> <th class="text-center"><span>Results</span></th> <th class="text-right"><span>Date</span></th> <th class="text-center"><span>Stars</span></th> </tr> </thead> </table> </div> <script> const DATATABLE_PAPERS_FILTER_NAME = 'papermethod__method_id'; const DATATABLE_PAPERS_FILTER_VALUE = '336'; </script> </div> <div id="tasks"> <h4 style="margin-bottom: 0.5rem">Tasks</h4> <hr> <div class="row"> <div class="col-lg-6"> <figure class="highcharts-figure"> <div id="usage-container"></div> </figure> </div> <div class="col-lg-6 task-methods"> <table> <tr> <th>Task</th> <th class="text-right">Papers</th> <th class="text-right">Share</th> </tr> <tr> <td><span class="dot" style="background-color: #2f7ed8"></span> <a href="/task/audio-generation">Audio Generation</a> </td> <td class="text-right">1</td> <td class="text-right">50.00%</td> </tr> <tr> <td><span class="dot" style="background-color: #0d233a"></span> <a href="/task/image-generation">Image Generation</a> </td> <td class="text-right">1</td> <td class="text-right">50.00%</td> </tr> </table> </div> </div> </div> <div id="trends"> <h4 style="margin-bottom: 0.5rem">Usage Over Time</h4> <hr> <figure style="margin-top: 2.5rem" class="highcharts-figure"> <div id="container"></div> </figure> <span class="experimental-note hidden-element"><span class=" icon-wrapper icon-ion" data-name="flask-outline"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-miterlimit="10" stroke-width="32" d="M176 48h160M118 304h276M208 48v93.48a64.09 64.09 0 0 1-9.88 34.18L73.21 373.49C48.4 412.78 76.63 464 123.08 464h265.84c46.45 0 74.68-51.22 49.87-90.51L313.87 175.66a64.09 64.09 0 0 1-9.87-34.18V48"/></svg></span> This feature is experimental; we are continuously improving our matching algorithm.</span> </div> <div id="components"> <h4 style="margin-bottom: 0.5rem">Components</h4> <hr> <table> <tr> <th>Component</th> <th>Type</th> <th class="hidden-element"> <div class="float-right"> <div class="dropdown edit-button"> <button class="dropdown-toggle badge badge-edit" type="button" id="compEditMenu" data-bs-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> <span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit </button> <div class="dropdown-menu dropdown-menu-end" aria-labelledby="compEditMenu" x-placement="bottom-end" style="position: absolute; transform: translate3d(55px, 35px, 0px); top: 0px; left: 0px; will-change: transform;"> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="add"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M256 112v288m144-144H112"/></svg></span> Add</a> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="remove"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M400 256H112"/></svg></span> Remove</a> </div> </div> </div> </th> </tr> <tr> <td><a href="/method/dcgan"> <div class="method-image"> <img src="https://production-media.paperswithcode.com/thumbnails/method/e9148b0d-3454-4d14-9e04-4bd61d423e4a.jpg"> DCGAN </div> </a> </td> <td> <a href="/methods/category/generative-models"> Generative Models </a> </td> <td class="hidden-element"> </td> </tr> <tr> <td><a href="/method/griffin-lim-algorithm"> <div class="method-image"> <img src="https://production-media.paperswithcode.com/thumbnails/method/method-0000000691-b9c5f6dd.jpg"> Griffin-Lim Algorithm </div> </a> </td> <td> <a href="/methods/category/phase-reconstruction"> Phase Reconstruction </a> </td> <td class="hidden-element"> </td> </tr> <tr> <td><a href="/method/phase-shuffle"> <div class="method-image"> <img src="https://production-media.paperswithcode.com/thumbnails/method/method-0000000689-1651d6f3.jpg"> Phase Shuffle </div> </a> </td> <td> <a href="/methods/category/audio-artifact-removal"> Audio Artifact Removal </a> </td> <td class="hidden-element"> </td> </tr> <tr> <td><a href="/method/tanh-activation"> <div class="method-image"> <img src="https://production-media.paperswithcode.com/thumbnails/method/method-0000000494-223578ca_rde7ctJ.jpg"> Tanh Activation </div> </a> </td> <td> <a href="/methods/category/activation-functions"> Activation Functions </a> </td> <td class="hidden-element"> </td> </tr> <tr> <td><a href="/method/wgan-gp-loss"> <div class="method-image"> <img src="https://production-media.paperswithcode.com/thumbnails/method/method-0000000014-ceed4e75.jpg"> WGAN-GP Loss </div> </a> </td> <td> <a href="/methods/category/loss-functions"> Loss Functions </a> </td> <td class="hidden-element"> </td> </tr> </table> </div> <div class="collections"> <h4> Categories <div class="float-right"> <div class="dropdown edit-button"> <button class="dropdown-toggle badge badge-edit" type="button" id="evalEditMenu" data-bs-toggle="dropdown" aria-haspopup="true" aria-expanded="false"> <span class=" icon-wrapper icon-fa icon-fa-solid" data-name="edit"><svg viewBox="0 0 576 514.999" xmlns="http://www.w3.org/2000/svg"><path d="M402.6 85.198l90.2 90.2c3.8 3.8 3.8 10 0 13.8l-218.399 218.4-92.8 10.3c-12.4 1.4-22.9-9.1-21.5-21.5l10.3-92.8 218.4-218.4c3.799-3.8 10-3.8 13.799 0zm162-22.9c15.2 15.2 15.2 39.9 0 55.2l-35.4 35.4c-3.8 3.8-10 3.8-13.8 0l-90.2-90.2c-3.8-3.8-3.8-10 0-13.8l35.4-35.4c15.3-15.2 40-15.2 55.2 0zM384 348.198c0-3.2 1.3-6.2 3.5-8.5l40-40c7.6-7.5 20.5-2.2 20.5 8.5v157.8c0 26.5-21.5 48-48 48H48c-26.5 0-48-21.5-48-48v-352c0-26.5 21.5-48 48-48h285.8c10.7 0 16.1 12.9 8.5 20.5l-40 40c-2.3 2.2-5.3 3.5-8.5 3.5H64v320h320v-101.8z"/></svg></span> Edit </button> <div class="dropdown-menu dropdown-menu-end" aria-labelledby="evalEditMenu" x-placement="bottom-end" style="position: absolute; transform: translate3d(55px, 35px, 0px); top: 0px; left: 0px; will-change: transform;"> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="add"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M256 112v288m144-144H112"/></svg></span> Add</a> <a class="dropdown-item" href="#loginModal" data-bs-toggle="modal"> <span class=" icon-wrapper icon-ion" data-name="remove"><svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512"><path fill="none" stroke="#000" stroke-linecap="round" stroke-linejoin="round" stroke-width="32" d="M400 256H112"/></svg></span> Remove</a> </div> </div> </div><hr> </h4> </div> <div class="row"> <div class="col-md-12"> <ul class="list-unstyled"> <li> <a href="/methods/category/generative-audio-models"> <span class="badge badge-primary"> <img src="https://production-media.paperswithcode.com/tasks/default.gif"> <span>Generative Audio Models</span> </span> </a> </li> </ul> </div> </div> </div> </div> <script id="task_data" type="application/json">[{"name": "Audio Generation", "slug": "audio-generation", "papers": 1, "y": 50.0, "dot_color": "#2f7ed8"}, {"name": "Image Generation", "slug": "image-generation", "papers": 1, "y": 50.0, "dot_color": "#0d233a"}]</script> <script id="time_series_data" type="application/json">[{"name": "SpecGAN", "data": [{"time": "2017-12-31 00:00:00", "prop": 0.0}, {"time": "2018-03-31 00:00:00", "prop": 3.9306631028654534e-05}, {"time": "2018-06-30 00:00:00", "prop": 0.0}, {"time": "2018-09-30 00:00:00", "prop": 0.0}, {"time": "2018-12-31 00:00:00", "prop": 0.0}, {"time": "2019-03-31 00:00:00", "prop": 0.0}, {"time": "2019-06-30 00:00:00", "prop": 0.0}, {"time": "2019-09-30 00:00:00", "prop": 0.0}, {"time": "2019-12-31 00:00:00", "prop": 0.0}, {"time": "2020-03-31 00:00:00", "prop": 0.0}, {"time": "2020-06-30 00:00:00", "prop": 0.0}, {"time": "2020-09-30 00:00:00", "prop": 0.0}, {"time": "2020-12-31 00:00:00", "prop": 0.0}, {"time": "2021-03-31 00:00:00", "prop": 0.0}, {"time": "2021-06-30 00:00:00", "prop": 0.0}, {"time": "2021-09-30 00:00:00", "prop": 0.0}, {"time": "2021-12-31 00:00:00", "prop": 0.0}, {"time": "2022-03-31 00:00:00", "prop": 0.0}, {"time": "2022-06-30 00:00:00", "prop": 0.0}, {"time": "2022-09-30 00:00:00", "prop": 0.0}, {"time": "2022-12-31 00:00:00", "prop": 0.0}, {"time": "2023-03-31 00:00:00", "prop": 0.0}, {"time": "2023-06-30 00:00:00", "prop": 0.0}, {"time": "2023-09-30 00:00:00", "prop": 0.0}, {"time": "2023-12-31 00:00:00", "prop": 0.0}, {"time": "2024-03-31 00:00:00", "prop": 0.0}, {"time": "2024-06-30 00:00:00", "prop": 0.0}, {"time": "2024-09-30 00:00:00", "prop": 0.0}]}, {"name": "WaveNet", "data": [{"time": "2017-12-31 00:00:00", "prop": 0.00011568272085759457}, {"time": "2018-03-31 00:00:00", "prop": 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