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/gradium/stt.py

@@ -27,6 +27,7 @@ from pipecat.frames.frames import (
     VADUserStoppedSpeakingFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.stt_latency import GRADIUM_TTFS_P99
 from pipecat.services.stt_service import WebsocketSTTService
 from pipecat.transcriptions.language import Language, resolve_language
 from pipecat.utils.time import time_now_iso8601
@@ -94,6 +95,7 @@ class GradiumSTTService(WebsocketSTTService):
         api_endpoint_base_url: str = "wss://eu.api.gradium.ai/api/speech/asr",
         params: Optional[InputParams] = None,
         json_config: Optional[str] = None,
+        ttfs_p99_latency: Optional[float] = GRADIUM_TTFS_P99,
         **kwargs,
     ):
         """Initialize the Gradium STT service.
@@ -107,9 +109,11 @@ class GradiumSTTService(WebsocketSTTService):
                 .. deprecated:: 0.0.101
                     Use `params` instead for type-safe configuration.
 
+            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 STTService class.
         """
-        super().__init__(sample_rate=SAMPLE_RATE, **kwargs)
+        super().__init__(sample_rate=SAMPLE_RATE, ttfs_p99_latency=ttfs_p99_latency, **kwargs)
 
         if json_config is not None:
             import warnings