{"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":"Detects voiced versus unvoiced segments in audio by wrapping Google's WebRTC Voice Activity Detector with pre-built binary wheels for Windows, macOS, and Linux.","skillfed_tags":["audio-processing","speech-recognition","webrtc"],"use_cases":["Filter silence from audio recordings before sending to a speech-to-text service to reduce processing cost and latency.","Segment a continuous audio stream into voiced and unvoiced regions for telephony or voice call analysis.","Preprocess microphone input in real-time speech recognition to skip processing during silence.","Detect speech activity in surveillance or meeting recordings to identify when participants are speaking.","Build a voice activity detector for audio quality assessment or speaker diarization pipelines."],"what_it_does":"This package wraps Google's WebRTC Voice Activity Detector, a fast and accurate classifier that determines whether a short audio segment contains speech or silence. It accepts 16-bit mono PCM audio at standard sample rates and returns a boolean result, with tunable aggressiveness (0\u20133) to control sensitivity to non-speech sounds. The package is distributed with pre-compiled binary wheels, eliminating the need to build the underlying C extension on Windows, macOS, and Linux across multiple architectures and CPU types.\n\nThe VAD is commonly used as a preprocessing step in speech recognition pipelines, telephony systems, and audio analysis workflows where you need to filter out silence or identify voiced regions before further processing. With no runtime dependencies and a simple API, it integrates easily into Python audio applications.","worth_installing":"Yes. The package is stable (Production/Stable status), has no known vulnerabilities, zero runtime dependencies, and ships with pre-built wheels that eliminate compilation friction on major platforms. The aging maintenance status is acceptable for a mature, focused tool with a narrow scope. Install it if you need reliable voice activity detection in Python."},"id":"webrtcvad-wheels","links":{"html":"https://skillfed.io/packages/webrtcvad-wheels","md":"https://skillfed.io/packages/webrtcvad-wheels.md","pypi":"https://pypi.org/project/webrtcvad-wheels/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2024-09-05","license_spdx":null,"license_treatment":"permissive","name":"webrtcvad-wheels","python_support":"unspecified","summary":"Python interface to the Google WebRTC Voice Activity Detector (VAD) [released with binary wheels!]"},"popularity":{"monthly_downloads":528543,"position":6164,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.14"}