Extracting Speech Segments with Silero VAD and ONNX Runtime
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Hello, everyone. Have you ever wanted to keep only the parts of a recording where someone is speaking? Finding silence before transcription can reduce downstream work and divide a long recording into more manageable pieces. Today, I will use the ONNX model from Silero VAD to detect speech in a roughly 14-second conversation and extract each segment as a WAV file. What I Tested This lab uses FFmpeg to decode an MP3 conversation between two speakers into a 16 kHz mono waveform. It then feeds the…
1Key Takeaways
- Have you ever wanted to keep only the parts of a recording where someone is speaking?
- Finding silence before transcription can reduce downstream work and divide a long recording into more manageable pieces.
- Today, I will use the ONNX model from Silero VAD to detect speech in a roughly 14-second conversation and extract each segment as a WAV file.
- What I Tested This lab uses FFmpeg to decode an MP3 conversation between two speakers into a 16 kHz mono waveform.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that have you ever wanted to keep only the parts of a recording where someone is speaking?
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