Improve user turn stop timing by triggering timeout from VAD stop

Refactor TranscriptionUserTurnStopStrategy and TurnAnalyzerUserTurnStopStrategy
to use VADUserStoppedSpeakingFrame as the ground truth for when speech ended,
rather than triggering timeouts from transcription frames.

src/pipecat/services/openai/stt.py

@@ -34,6 +34,7 @@ from pipecat.frames.frames import (
     VADUserStoppedSpeakingFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.stt_latency import OPENAI_REALTIME_TTFS_P99, OPENAI_TTFS_P99
 from pipecat.services.stt_service import WebsocketSTTService
 from pipecat.services.whisper.base_stt import BaseWhisperSTTService, Transcription
 from pipecat.transcriptions.language import Language
@@ -64,6 +65,7 @@ class OpenAISTTService(BaseWhisperSTTService):
         language: Optional[Language] = Language.EN,
         prompt: Optional[str] = None,
         temperature: Optional[float] = None,
+        ttfs_p99_latency: Optional[float] = OPENAI_TTFS_P99,
         **kwargs,
     ):
         """Initialize OpenAI STT service.
@@ -75,6 +77,8 @@ class OpenAISTTService(BaseWhisperSTTService):
             language: Language of the audio input. Defaults to English.
             prompt: Optional text to guide the model's style or continue a previous segment.
             temperature: Optional sampling temperature between 0 and 1. Defaults to 0.0.
+            ttfs_p99_latency: P99 latency from speech end to final transcript in seconds.
+                Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark
             **kwargs: Additional arguments passed to BaseWhisperSTTService.
         """
         super().__init__(
@@ -84,6 +88,7 @@ class OpenAISTTService(BaseWhisperSTTService):
             language=language,
             prompt=prompt,
             temperature=temperature,
+            ttfs_p99_latency=ttfs_p99_latency,
             **kwargs,
         )
 
@@ -162,6 +167,7 @@ class OpenAIRealtimeSTTService(WebsocketSTTService):
         turn_detection: Optional[Union[dict, Literal[False]]] = False,
         noise_reduction: Optional[Literal["near_field", "far_field"]] = None,
         should_interrupt: bool = True,
+        ttfs_p99_latency: Optional[float] = OPENAI_REALTIME_TTFS_P99,
         **kwargs,
     ):
         """Initialize the OpenAI Realtime STT service.
@@ -187,6 +193,8 @@ class OpenAIRealtimeSTTService(WebsocketSTTService):
             should_interrupt: Whether to interrupt bot output when
                 speech is detected by server-side VAD. Only applies when
                 turn detection is enabled. Defaults to True.
+            ttfs_p99_latency: P99 latency from speech end to final transcript in seconds.
+                Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark
             **kwargs: Additional arguments passed to parent
                 WebsocketSTTService.
         """
@@ -196,7 +204,10 @@ class OpenAIRealtimeSTTService(WebsocketSTTService):
                 "Install it with: pip install pipecat-ai[openai]"
             )
 
-        super().__init__(**kwargs)
+        super().__init__(
+            ttfs_p99_latency=ttfs_p99_latency,
+            **kwargs,
+        )
 
         self._api_key = api_key
         self._base_url = base_url