{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/5"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Human Machine Interfaces","url":"https://skillfed.io/packages/category/scientific-engineering-human-machine-interfaces"}],"enrichment":{"capability":"Provides a Python interface to Google's WebRTC Voice Activity Detector, classifying audio frames as voiced or unvoiced for speech recognition and telephony applications.","skillfed_tags":["audio-processing","speech-detection"],"use_cases":["Preprocessing audio streams for automatic speech recognition by filtering out silence before sending to a speech-to-text service.","Segmenting recorded phone calls or voice messages to extract only the voiced portions for analysis or transcription.","Real-time voice activity detection in VoIP or conferencing applications to trigger recording or transmission only when speech is detected.","Training or evaluating speech detection models by labeling audio data as voiced or unvoiced at the frame level."],"what_it_does":"webrtcvad is a Python binding to Google's WebRTC Voice Activity Detector, a classifier that determines whether short audio frames contain speech or silence. It accepts 16-bit mono PCM audio at fixed sample rates (8000, 16000, or 32000 Hz) in frames of 10, 20, or 30 milliseconds, and returns a boolean indicating whether speech is present. The detector supports aggressiveness levels (0\u20133) to tune sensitivity.\n\nThe package is used in speech recognition pipelines, telephony systems, and audio preprocessing workflows where you need to filter out silence or identify speech segments before further processing. It wraps a mature, well-regarded algorithm from the WebRTC project, but the Python wrapper itself has not been updated since 2017-01-07, creating uncertainty about compatibility with modern Python toolchains and whether better-maintained alternatives now exist.","worth_installing":"Yes, with conditions. The underlying WebRTC VAD algorithm is mature and well-regarded. However, high install friction (compiled extension), dormancy since 2017-01-07, and uncertainty about modern Python compatibility mean you should verify it builds on your target platform and consider whether a more recently maintained alternative better suits your needs before committing."},"id":"webrtcvad","links":{"html":"https://skillfed.io/packages/webrtcvad","md":"https://skillfed.io/packages/webrtcvad.md","pypi":"https://pypi.org/project/webrtcvad/"},"maintenance":{"status":"dormant"},"meta":{"latest_release":"2017-01-07","license_spdx":null,"license_treatment":"permissive","name":"webrtcvad","python_support":"unspecified","summary":"Python interface to the Google WebRTC Voice Activity Detector (VAD)"},"popularity":{"monthly_downloads":480417,"position":6430,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.10"}