Addressing code review comments

This commit is contained in:
marcus-daily
2026-01-09 13:44:44 +00:00
committed by Marcus
parent 35a99f92ab
commit b075502c4c
3 changed files with 22 additions and 18 deletions

View File

@@ -116,6 +116,18 @@ class BaseTurnAnalyzer(ABC):
"""
pass
def on_vad_start_secs_updated(self, vad_start_secs: float):
"""Invoked when the VAD start trigger time is updated.
The turn analyzer may choose to change its buffer size depending
on this value.
Args:
vad_start_secs (float): The number of seconds of voice activity
before triggering the user speaking event.
"""
pass
@abstractmethod
def clear(self):
"""Reset the turn analyzer to its initial state."""

View File

@@ -35,15 +35,11 @@ class SmartTurnParams(BaseTurnParams):
Parameters:
stop_secs: Maximum silence duration in seconds before ending turn.
pre_speech_ms: Milliseconds of audio to include before speech starts.
vad_start_secs: Seconds VAD waits before confirming speech start (e.g. VAD STARTING window).
This is added to `pre_speech_ms` at inference slicing time so Smart Turn can include
the initial audio that occurred while VAD was still confirming speech.
max_duration_secs: Maximum duration in seconds for audio segments.
"""
stop_secs: float = STOP_SECS
pre_speech_ms: float = PRE_SPEECH_MS
vad_start_secs: float = 0.0
max_duration_secs: float = MAX_DURATION_SECONDS
@@ -82,6 +78,7 @@ class BaseSmartTurn(BaseTurnAnalyzer):
# Thread executor that will run the model. We only need one thread per
# analyzer because one analyzer just handles one audio stream.
self._executor = ThreadPoolExecutor(max_workers=1)
self._vad_start_secs: float = 0.0
@property
def speech_triggered(self) -> bool:
@@ -165,6 +162,9 @@ class BaseSmartTurn(BaseTurnAnalyzer):
logger.debug(f"End of Turn result: {state}")
return state, result
def on_vad_start_secs_updated(self, vad_start_secs: float):
self._vad_start_secs = vad_start_secs
def clear(self):
"""Reset the turn analyzer to its initial state."""
self._clear(EndOfTurnState.COMPLETE)
@@ -185,7 +185,7 @@ class BaseSmartTurn(BaseTurnAnalyzer):
return state, None
# Extract recent audio segment for prediction
effective_pre_speech_ms = self._params.pre_speech_ms + (self._params.vad_start_secs * 1000)
effective_pre_speech_ms = self._params.pre_speech_ms + (self._vad_start_secs * 1000)
start_time = self._speech_start_time - (effective_pre_speech_ms / 1000)
start_index = 0
for i, (t, _) in enumerate(audio_buffer):

View File

@@ -108,20 +108,12 @@ class TurnAnalyzerUserTurnStopStrategy(BaseUserTurnStopStrategy):
async def _handle_speech_control_params(self, frame: SpeechControlParamsFrame):
"""Sync Smart Turn pre-speech buffering with VAD start delay.
In the new user-turn-strategies pipeline, `VADUserStartedSpeakingFrame`
is emitted only once VAD has *confirmed* speech (after `vad_params.start_secs`).
Smart Turn should still include the initial audio collected during that
confirmation window, so we record it in `SmartTurnParams.vad_start_secs` and
add it at inference slicing time (preserving `pre_speech_ms` semantics).
`VADUserStartedSpeakingFrame` is emitted only once VAD has confirmed speech
(after `vad_params.start_secs`). Smart Turn should still include the initial
audio collected during that confirmation window, so we let the analyzer know
when this value has changed.
"""
if not frame.vad_params:
return
params = self._turn_analyzer.params
if not isinstance(params, SmartTurnParams):
return
params.vad_start_secs = frame.vad_params.start_secs
self._turn_analyzer.on_vad_start_secs_updated(frame.vad_params.start_secs)
async def _handle_input_audio(self, frame: InputAudioRawFrame):
"""Handle input audio to check if the turn is completed."""