# Huggingface Speech-to-Speech VAD Turn-Taking Parameters: Configuring --thresh, --min_speech_ms, and --min_silence_ms

> Discover how to control Huggingface Speech-to-Speech VAD turn-taking with --thresh, --min_speech_ms, and --min_silence_ms parameters. Optimize your audio processing.

- Repository: [Hugging Face/speech-to-speech](https://github.com/huggingface/speech-to-speech)
- Tags: how-to-guide
- Published: 2026-07-30

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**The `--thresh`, `--min_speech_ms`, and `--min_silence_ms` command-line arguments control Voice Activity Detection (VAD) turn-taking by setting the confidence threshold for speech detection, the minimum duration of active speech required to start a turn, and the silence interval needed to close a speech segment.**

 The huggingface/speech-to-speech repository implements real-time conversation flow through three critical VAD turn-taking parameters that determine when user speech begins and ends. These parameters, accessed via `VADHandlerArguments` and applied in `VADHandler`, prevent false triggers from background noise and ensure natural pause detection. Understanding how to configure `--thresh`, `--min_speech_ms`, and `--min_silence_ms` allows precise tuning of turn boundaries for voice-based AI interactions.

 ## How --thresh Controls Speech Detection Confidence

 The `--thresh` parameter sets the probability threshold for the underlying Silero VAD model, with a default value of **0.6**. Stored in `VADHandlerArguments.thresh`, this value is assigned to `VADIterator.threshold` during the `setup()` method in [`src/speech_to_speech/VAD/vad_handler.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/VAD/vad_handler.py). Frames with speech probability below this threshold are classified as silence, while frames above it indicate active speech.

 Higher values make the system more conservative, reducing false positives but potentially delaying detection of low-energy speech. Lower values increase sensitivity to quiet speech but may trigger on non-speech noise. The handler can update this threshold at runtime via `_apply_runtime_turn_detection()`, enabling adaptive sensitivity without pipeline restarts.

 ## How --min_speech_ms Filters Short Utterances

 The `--min_speech_ms` parameter defines the minimum length of active speech required before the system emits a `SpeechStartedEvent`, defaulting to **384 ms**. This value, stored as `VADHandlerArguments.min_speech_ms`, prevents brief noises or false positives from triggering new conversation turns.

 In [`src/speech_to_speech/VAD/vad_handler.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/VAD/vad_handler.py), the handler consults this parameter in `_active_speech_min_ms` and `_ensure_turn_for_speech_start` to verify that `effective_active_speech_duration_ms >= active_speech_min_ms` before confirming a turn has started. The parameter also supports continuation logic through `min_speech_continuation_ms`, allowing shorter follow-up utterances when a turn is already active.

 ## How --min_silence_ms Defines Turn Boundaries

 The `--min_silence_ms` parameter specifies the shortest silence interval that the VAD treats as a break between speech segments, with a default of **64 ms**. When silence exceeds this duration, the current speech segment closes and the handler emits a `SpeechStoppedEvent`, signaling that a new turn may begin.

 Stored in `VADHandlerArguments.min_silence_ms`, this value is passed to `VADIterator.min_silence_duration_ms` in the `setup()` method. Pauses shorter than this threshold keep the speech segment open, effectively merging consecutive utterances into a single continuous turn.

 ## Source Code Implementation

 The turn-taking logic is distributed across three key files:

 - **[`src/speech_to_speech/arguments_classes/vad_arguments.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/arguments_classes/vad_arguments.py)** — Defines `VADHandlerArguments` with defaults (`thresh=0.6`, `min_speech_ms=384`, `min_silence_ms=64`) and CLI help text.
 - **[`src/speech_to_speech/VAD/vad_handler.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/VAD/vad_handler.py)** — Implements turn-start and turn-end heuristics, emitting `SpeechStartedEvent` and `SpeechStoppedEvent` based on the three parameters.
 - **[`src/speech_to_speech/VAD/vad_iterator.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/VAD/vad_iterator.py)** — Low-level Silero VAD processing that receives `threshold` and `min_silence_duration_ms` from the handler.

 ## Configuration Examples

 ### Direct Handler Instantiation

 ```python
 from speech_to_speech.VAD.vad_handler import VADHandler
 from threading import Event

 listen_event = Event()
 listen_event.set()

 handler = VADHandler()
 handler.setup(
     should_listen=listen_event,
     thresh=0.75,            # More conservative detection

     min_speech_ms=500,      # Require 500ms to start turn

     min_silence_ms=120,     # End turn after 120ms silence

 )
 ```

 ### Using Argument Classes

 ```python
 from speech_to_speech.arguments_classes.vad_arguments import VADHandlerArguments

 args = VADHandlerArguments(
     thresh=0.55,            # More sensitive

     min_speech_ms=300,      # Shutter utterances accepted

     min_silence_ms=80,      # Shorter pauses allowed

 )

 print(args)  # VADHandlerArguments(thresh=0.55, ..., min_speech_ms=300, min_silence_ms=80)

 ```

 ### Runtime Updates

 ```python
 # Update parameters dynamically without restarting

 handler._apply_runtime_turn_detection(new_config)
 ```

 ## Summary

 - **`--thresh`** (default 0.6) sets the VAD model confidence threshold in `VADIterator.threshold`; higher values reduce false positives but may miss quiet speech.
 - **`--min_speech_ms`** (default 384 ms) prevents short noises from triggering turns by requiring minimum active speech duration before emitting `SpeechStartedEvent`.
 - **`--min_silence_ms`** (default 64 ms) determines the pause length needed to close a speech segment and trigger `SpeechStoppedEvent`, allowing a new turn to begin.
 - These parameters are defined in `VADHandlerArguments`, applied in `VADHandler.setup()`, and executed in `VADIterator` within `src/speech_to_speech/VAD/`.

 ## Frequently Asked Questions

 ### What happens if --min_speech_ms is set too low?

 Setting `--min_speech_ms` below the default 384 ms increases responsiveness to short utterances but raises the risk of triggering turns on coughs, breaths, or transient background noise. Values below 100 ms may cause excessive turn-taking events and fragment the conversation flow.

 ### How does --min_silence_ms affect perceived latency?

 The `--min_silence_ms` parameter directly impacts how quickly the system recognizes a completed turn. Lower values (e.g., 50 ms) reduce end-of-turn latency but risk splitting single utterances with natural pauses into multiple turns, while higher values (e.g., 300 ms) ensure complete captures but introduce noticeable gaps before the system responds.

 ### Can VAD parameters be changed without restarting the application?

 Yes. According to the implementation in [`src/speech_to_speech/VAD/vad_handler.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/VAD/vad_handler.py), the `VADHandler._apply_runtime_turn_detection()` method supports dynamic updates to `thresh` and other turn-detection parameters during active audio processing sessions.

 ### Where are the default values for these VAD parameters defined?

 Default values are defined in [`src/speech_to_speech/arguments_classes/vad_arguments.py`](https://github.com/huggingface/speech-to-speech/blob/main/src/speech_to_speech/arguments_classes/vad_arguments.py) within the `VADHandlerArguments` dataclass: `thresh=0.6`, `min_speech_ms=384`, and `min_silence_ms=64`.