{"schema":"record/v1","id":"art_01M5NCKJ16SS7ES5ZK9678Q520","type":"article","revision":1,"etag":"\"r1.s0\"","title":"What are FFmpeg arnndn (RNN speech denoise), adeclick and adeclip for, and which options let you hear what they remove?","summary":"Problem: choose between a model-based denoiser and click/clip repair in an FFmpeg chain. Conditions: FFmpeg filter docs. Method: arnndn reduces noise from speech using recurrent neural networks; the model file option is always required (you must supply a trained model file); mix sets how much processed signal is blended into the output, range -1 to 1, default 1, and negative values keep the removed noise, with -1 letting you hear the actual noise removed. adeclick removes impulsive noise; samples detected as impulsive are replaced with interpolated samples using autoregressive modelling; options include window 10-100 ms (default 55), overlap 50-95 percent (default 75), arorder 0-25 percent (default 2) and threshold 1-100 (default 2; lower detects more samples as clicks). adeclip is the companion for clipped samples. Use (inference): run adeclick before denoise when clicks are sparse, keep threshold at default and lower it only if clicks remain, and use arnndn mix between 0.6 and 1 t...","status":"active","body":{"text":"Problem: choose between a model-based denoiser and click/clip repair in an FFmpeg chain. Conditions: FFmpeg filter docs. Method: arnndn reduces noise from speech using recurrent neural networks; the model file option is always required (you must supply a trained model file); mix sets how much processed signal is blended into the output, range -1 to 1, default 1, and negative values keep the removed noise, with -1 letting you hear the actual noise removed. adeclick removes impulsive noise; samples detected as impulsive are replaced with interpolated samples using autoregressive modelling; options include window 10-100 ms (default 55), overlap 50-95 percent (default 75), arorder 0-25 percent (default 2) and threshold 1-100 (default 2; lower detects more samples as clicks). adeclip is the companion for clipped samples. Use (inference): run adeclick before denoise when clicks are sparse, keep threshold at default and lower it only if clicks remain, and use arnndn mix between 0.6 and 1 to retain some natural room if speech sounds sterile. Failure modes: lowering threshold too far treats consonants as clicks; RNN denoise can alter breaths and fricatives. Limitations: the docs do not name a recommended model or any quality figures; the order advice is mine.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.\n\nLimitations: Option semantics from docs; ordering and values are inference.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://ffmpeg.org/ffmpeg-filters.html","note":"8.50 arnndn; 8.50 arnndn; 8.9 adeclick"}]},"categories":["T10","T13"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://ffmpeg.org/ffmpeg-filters.html","claim":"Problem: choose between a model-based denoiser and click/clip repair in an FFmpeg chain. Conditions: FFmpeg filter docs. Method: arnndn reduces noise from speech using recurrent neural networks; the model file option is always required (you must supply a trained model file); mix sets how much processed signal is blended into the output, range -1 to 1, default 1, and negative values keep the removed noise, with -1 letting you hear the actual noise removed. adeclick removes impulsive noise; samples detected as impulsive are replaced with interpolated samples using autoregressive modelling; options include window 10-100 ms (default 55), overlap 50-95 percent (default 75), arorder 0-25 percent (default 2) and threshold 1-100 (default 2; lower detects more samples as clicks). adeclip is the companion for clipped samples. Use (inference): run adeclick before denoise when clicks are sparse, keep threshold at default and lower it only if clicks remain, and use arnndn mix between 0.6 and 1 to retain some natural room if speech sounds sterile. Failure modes: lowering threshold too far treats consonants as clicks; RNN denoise can alter breaths and fricatives. 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Conditions: FFmpeg filter docs. Method: arnndn reduces noise from speech using recurrent neural networks; the model file option is always required (you must supply a trained model file); mix sets how much processed signal is blended into the output, range -1 to 1, default 1, and negative values keep the removed noise, with -1 letting you hear the actual noise removed. adeclick removes impulsive noise; samples detected as impulsive are replaced with interpolated samples using autoregressive modelling; options include window 10-100 ms (default 55), overlap 50-95 percent (default 75), arorder 0-25 percent (default 2) and threshold 1-100 (default 2; lower detects more samples as clicks). adeclip is the companion for clipped samples. Use (inference): run adeclick before denoise when clicks are sparse, keep threshold at default and lower it only if clicks remain, and use arnndn mix between 0.6 and 1 to retain some natural room if speech sounds sterile. Failure modes: lowering threshold too far treats consonants as clicks; RNN denoise can alter breaths and fricatives. Limitations: the docs do not name a recommended model or any quality figures; the order advice is mine.\n\nCurator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.\n\nLimitations: Option semantics from docs; ordering and values are inference.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://ffmpeg.org/ffmpeg-filters.html","note":"8.50 arnndn; 8.50 arnndn; 8.9 adeclick"}]},"tags":[],"type":"article","links":[],"title":"What are FFmpeg arnndn (RNN speech denoise), adeclick and adeclip for, and which options let you hear what they remove?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"Problem: choose between a model-based denoiser and click/clip repair in an FFmpeg chain. Conditions: FFmpeg filter docs. Method: arnndn reduces noise from speech using recurrent neural networks; the model file option is always required (you must supply a trained model file); mix sets how much processed signal is blended into the output, range -1 to 1, default 1, and negative values keep the removed noise, with -1 letting you hear the actual noise removed. adeclick removes impulsive noise; samples detected as impulsive are replaced with interpolated samples using autoregressive modelling; options include window 10-100 ms (default 55), overlap 50-95 percent (default 75), arorder 0-25 percent (default 2) and threshold 1-100 (default 2; lower detects more samples as clicks). adeclip is the companion for clipped samples. Use (inference): run adeclick before denoise when clicks are sparse, keep threshold at default and lower it only if clicks remain, and use arnndn mix between 0.6 and 1 t...","evidence":{"claims":[{"url":"https://ffmpeg.org/ffmpeg-filters.html","claim":"Problem: choose between a model-based denoiser and click/clip repair in an FFmpeg chain. Conditions: FFmpeg filter docs. Method: arnndn reduces noise from speech using recurrent neural networks; the model file option is always required (you must supply a trained model file); mix sets how much processed signal is blended into the output, range -1 to 1, default 1, and negative values keep the removed noise, with -1 letting you hear the actual noise removed. adeclick removes impulsive noise; samples detected as impulsive are replaced with interpolated samples using autoregressive modelling; options include window 10-100 ms (default 55), overlap 50-95 percent (default 75), arorder 0-25 percent (default 2) and threshold 1-100 (default 2; lower detects more samples as clicks). adeclip is the companion for clipped samples. Use (inference): run adeclick before denoise when clicks are sparse, keep threshold at default and lower it only if clicks remain, and use arnndn mix between 0.6 and 1 to retain some natural room if speech sounds sterile. Failure modes: lowering threshold too far treats consonants as clicks; RNN denoise can alter breaths and fricatives. Limitations: the docs do not name a recommended model or any quality figures; the order advice is mine.","locator":"8.50 arnndn; 8.50 arnndn; 8.9 adeclick","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T10","T13"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":2,"topic_ids":["CAT:T13.08"],"confidence":"Option semantics from docs; ordering and values are inference.","limitations":["Option semantics from docs; ordering and values are inference.","Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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