VAD (Voice Activity Detection)

Definition:

Voice Activity Detection detects valid speech segments in an audio stream and distinguishes between speech segments (such as speech) and non-speech segments (such as silence, noise, breathing).

Core functions:

Trigger mechanism: Start subsequent processing (such as voice recognition and recording) only when voice is detected, saving computing power and storage resources.

Speech segmentation: In speech-to-text scenarios, the starting and ending points of speech are automatically marked to improve the efficiency of transcription (such as reducing invalid processing of silent segments).

Technical realization:

Traditional methods: based on energy threshold (the energy of the speech segment is higher than the noise), zero crossing rate (the frequency of the speech signal changes faster) and other features.

AI method: Use neural network models such as LSTM and CNN, combined with Mel spectrum features, to improve detection accuracy in complex environments.

Application cases:

Smart Watch: Wake up the voice assistant only when the user is speaking, avoiding false activation (such as false triggering in daily activities).

Recording equipment: automatically skip the long silence in the meeting, save only the effective speech content, reduce the file volume.

Technical value:

As an "energy-saving switch" for voice processing, it reduces device power consumption (such as extended headset standby time) and improves the accuracy of interactive response.