Understanding VAD

This document explains the Voice Activity Detection (VAD) feature in our Realtime Speech API.

Overview

Voice Activity Detection (VAD) is a crucial component in speech processing systems. It is a signal processing technique used to detect the presence or absence of human speech in an audio signal. By differentiating between speech and non-speech segments, VAD optimizes the performance of real-time speech applications, including Automatic Speech Recognition (ASR), Voice over IP (VoIP), and conversational AI.

Key Parameters in VAD

The following parameters are available for configuring VAD in your Real-Time Speech API:

Turn Detection

• Configuration: Turn detection is an optional feature that can be enabled or disabled. Setting it to null disables turn detection.
• Server VAD: This is the currently supported type of turn detection. It detects the start and end of speech based on audio volume and responds at the end of the user’s speech.

Parameters for Turn Detection

Parameter	Description	Default Value	Range
type	Type of turn detection. Currently, only server_vad is supported.	server_vad	N/A
threshold	Activation threshold for VAD (0.0 to 1.0). Higher values require louder audio to activate.	0.5	0.0 - 1.0
prefix_padding_ms	Amount of audio to include before the VAD-detected speech (in milliseconds).	300ms	N/A
silence_duration_ms	Duration of silence to detect speech stop (in milliseconds). Shorter values improve response time.	500ms	N/A
create_response	Whether to automatically generate a response when VAD is enabled.	true	true/false

Explanation of Parameters

• threshold: Adjust this value based on the noise level of the environment. A higher threshold is ideal for noisy settings, ensuring the model activates only for significant audio inputs.
• prefix_padding_ms: Useful for capturing audio context before detected speech starts, providing smoother interactions.
• silence_duration_ms: This parameter controls the responsiveness of the system. Lower values result in faster responses but may cut off speech during short pauses.
• create_response: Enabling this ensures the system generates a response as soon as speech is detected and stops, streamlining interaction workflows.

By fine-tuning these parameters, users can optimize VAD performance for various real-time applications, ensuring precise and efficient voice interactions.