add speechmatics tts

This commit is contained in:
Aaron Ng
2025-10-29 14:53:20 +00:00
parent 493d6bf91e
commit 4050e8b7dc
3 changed files with 217 additions and 30 deletions

View File

@@ -0,0 +1,174 @@
#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
"""Speechmatics TTS service integration."""
import os
from typing import AsyncGenerator, Optional
import aiohttp
import numpy as np
from loguru import logger
from pydantic import BaseModel
from pipecat.frames.frames import (
ErrorFrame,
Frame,
TTSAudioRawFrame,
TTSStartedFrame,
TTSStoppedFrame,
)
from pipecat.services.tts_service import TTSService
from pipecat.utils.tracing.service_decorators import traced_tts
class SpeechmaticsTTSService(TTSService):
"""Speechmatics TTS service implementation.
This service provides text-to-speech synthesis using the Speechmatics HTTP API.
It converts text to speech and returns raw PCM audio data for real-time playback.
"""
class InputParams(BaseModel):
"""Configuration parameters for Speechmatics TTS service.
Parameters:
voice: Voice model to use for synthesis. Defaults to "sarah".
"""
voice: str = "sarah"
def __init__(
self,
*,
api_key: str | None = None,
base_url: str | None = None,
aiohttp_session: aiohttp.ClientSession | None = None,
sample_rate: Optional[int] = 16000,
params: InputParams | None = None,
**kwargs,
):
"""Initialize the Speechmatics TTS service.
Args:
api_key: Speechmatics API key for authentication. Uses environment variable
`SPEECHMATICS_API_KEY` if not provided.
base_url: Base URL for Speechmatics TTS API. Defaults to
`https://preview.tts.speechmatics.com`.
aiohttp_session: Shared aiohttp session for HTTP requests.
sample_rate: Audio sample rate in Hz. Defaults to 16000.
params: Optional[InputParams]: Input parameters for the service.
**kwargs: Additional arguments passed to TTSService.
"""
super().__init__(sample_rate=sample_rate, **kwargs)
# Service parameters
self._api_key: str = api_key or os.getenv("SPEECHMATICS_API_KEY")
self._base_url: str = base_url or "https://preview.tts.speechmatics.com"
self._session = aiohttp_session or aiohttp.ClientSession()
# Check we have required attributes
if not self._api_key:
raise ValueError("Missing Speechmatics API key")
if not self._base_url:
raise ValueError("Missing Speechmatics base URL")
# Default parameters
self._params = params or SpeechmaticsTTSService.InputParams()
# Set voice from parameters
self.set_voice(self._params.voice)
def can_generate_metrics(self) -> bool:
"""Check if this service can generate processing metrics.
Returns:
True, as Speechmatics service supports metrics generation.
"""
return True
@traced_tts
async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
"""Generate speech from text using Speechmatics' HTTP API.
Args:
text: The text to synthesize into speech.
Yields:
Frame: Audio frames containing the synthesized speech.
"""
logger.debug(f"{self}: Generating TTS [{text}]")
headers = {
"Authorization": f"Bearer {self._api_key}",
"Content-Type": "application/json",
}
payload = {
"text": text,
}
url = f"{self._base_url}/generate/{self._voice_id}?output_format=pcm_16000"
try:
await self.start_ttfb_metrics()
async with self._session.post(url, json=payload, headers=headers) as response:
if response.status != 200:
error_message = f"Speechmatics TTS error: HTTP {response.status}"
logger.error(error_message)
yield ErrorFrame(error=error_message)
return
await self.start_tts_usage_metrics(text)
yield TTSStartedFrame()
# Process the response in streaming chunks
first_chunk = True
buffer = b""
# Helper to move all complete 2-byte int16 samples from buffer into a frame
def _emit_complete_samples():
nonlocal buffer
if len(buffer) < 2:
return None
complete_samples = len(buffer) // 2
complete_bytes = complete_samples * 2
audio_data = buffer[:complete_bytes]
buffer = buffer[complete_bytes:] # Keep remaining bytes for next iteration
return TTSAudioRawFrame(
audio=audio_data,
sample_rate=self.sample_rate,
num_channels=1,
)
async for chunk in response.content.iter_any():
if not chunk:
continue
if first_chunk:
await self.stop_ttfb_metrics()
first_chunk = False
buffer += chunk
# Emit a frame for all complete samples currently in buffer
frame = _emit_complete_samples()
if frame:
yield frame
# Process any remaining bytes in buffer after streaming ends
frame = _emit_complete_samples()
if frame:
yield frame
except Exception as e:
logger.exception(f"Error generating TTS: {e}")
yield ErrorFrame(error=f"Speechmatics TTS error: {str(e)}")
finally:
yield TTSStoppedFrame()