{"id":25536,"date":"2023-01-07T15:28:58","date_gmt":"2023-01-07T15:28:58","guid":{"rendered":"https:\/\/jurn.link\/jurnsearch\/?p=25536"},"modified":"2025-12-20T22:27:54","modified_gmt":"2025-12-20T22:27:54","slug":"delete-small-pure-silences-in-an-audio-recording","status":"publish","type":"post","link":"https:\/\/jurn.link\/jurnsearch\/index.php\/2023\/01\/07\/delete-small-pure-silences-in-an-audio-recording\/","title":{"rendered":"Delete small pure silences in an audio recording"},"content":{"rendered":"<p>How to find and delete small pure silences in an audio recording?<\/p>\n<p>These silences are known in the audio recording trade as \u201cdropouts\u201d or \u201cRF hits\u201d, commonly caused by tiny failures in radio microphone transmissions. But they can also be caused by having to record on a desktop PC from a huge video that\u2019s streaming down to someone with a relatively poor Internet connection. The video playback stutters and stalls a bit. Each stall results in a perfectly silent pause in the recording.<\/p>\n<p>So let\u2019s assume you\u2019ve either captured a field audio recording using a flaky RF mic, or have captured the audio going through your desktop sound card by using something like Total Recorder. Either way you find there are silent skips, and now you need to delete these tiny bits of silence. All 250 of them. Automatically.<\/p>\n<p>The powerful audio repair suite iZotope RX 7 should help here, and do this for you in a few clicks. But rather surprisingly it doesn\u2019t have such a thing. You instead have to have a PhD in using its complex \u2018Ambience Match\u2019 and \u2018Spectral Repair\u2019 modules. There must be an easier way for non-professionals.<\/p>\n<p>There is. The quick, easy, automatic and free solution is actually (you guessed it) good old Windows desktop freeware. Here\u2019s the workflow\u2026<\/p>\n<p>1. In this case the freeware really is a dinosaur, or rather the Wavosaur. Download and run. Admire the groovy retro 1995-style icon with the dinosaur face. Actually it\u2019s not that old, and the Wavosaur\u2019s current version is July 2020.<\/p>\n<p>2. Load your .WAV file into the mighty mammal-munching maws of the Wavosaur. Then go: Tools | Silence Remove | Custom. It\u2019s that simple.<\/p>\n<p>3. \u201c-90\u201d = find real pure silence, not just lecture room \u2018ambience\u2019. \u201c0.25\u201d = the silence is only to be deleted if longer than 0.25 seconds. Run \u201cOK\u201d.<\/p>\n<p>4. Wavosaur will stomp through the .WAV and find and delete silence, also close up the resulting gaps. There is no notification this has been done, but it has. When you go to see if it worked, you won\u2019t be able to find all those former \u201cflat bits\u201d in the audio signal. Though the \u201cambient room noise\u201d heard in the speaker\u2019s pauses should still be there in the waveform.<\/p>\n<p>That\u2019s because they had a tiny bit of noise in them, lifting them above the -90db threshold needed for deletion.<\/p>\n<p>5. Now you can save and then load the cleaned .WAV into Ocenaudio (also freeware, and a great replacement for Audacity) and from there quickly save out to an .MP3 file.<\/p>\n<p>If you\u2019re going to do this a lot, note that Wavosaur can do MP3 export, but it first needs lame_enc.dll installed correctly.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>How to find and delete small pure silences in an audio recording? These silences are known in the audio recording &hellip;<\/p>\n<p><a href=\"https:\/\/jurn.link\/jurnsearch\/index.php\/2023\/01\/07\/delete-small-pure-silences-in-an-audio-recording\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[],"class_list":["post-25536","post","type-post","status-publish","format-standard","hentry","category-jurn-tips-and-tricks"],"_links":{"self":[{"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/posts\/25536","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/comments?post=25536"}],"version-history":[{"count":2,"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/posts\/25536\/revisions"}],"predecessor-version":[{"id":25812,"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/posts\/25536\/revisions\/25812"}],"wp:attachment":[{"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/media?parent=25536"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/categories?post=25536"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/jurn.link\/jurnsearch\/index.php\/wp-json\/wp\/v2\/tags?post=25536"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}