Adolfo Reyna
120 lines
4.4 KiB
Python
120 lines
4.4 KiB
Python
"""Text-to-speech using the macOS system voices.
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Drives the `say` binary rather than AVSpeechSynthesizer. `say` can render
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straight to signed 16-bit little-endian PCM at a chosen sample rate, which is
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exactly what the pipeline wants, and it avoids reading raw AVAudioPCMBuffer
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channel pointers through pyobjc.
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Note that Siri's voices are not reachable this way. Apple does not expose them
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to third-party apps; `say` and AVSpeechSynthesizer only see the voices listed
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under System Settings > Accessibility > Spoken Content.
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"""
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import asyncio
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import os
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import tempfile
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import wave
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from collections.abc import AsyncGenerator
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from loguru import logger
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from pipecat.audio.utils import create_stream_resampler
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from pipecat.frames.frames import ErrorFrame, Frame, TTSAudioRawFrame
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from pipecat.services.settings import TTSSettings
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from pipecat.services.tts_service import TTSService
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SAY = "/usr/bin/say"
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# Chunked so playback can start before the whole file is read.
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_CHUNK_FRAMES = 2400 # 100ms at 24kHz
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def available_voices() -> list[tuple[str, str]]:
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"""Return (name, language) for every installed system voice."""
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import AVFoundation as AV
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return [(v.name(), v.language()) for v in AV.AVSpeechSynthesisVoice.speechVoices()]
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def find_voice(name: str) -> tuple[str, str] | None:
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"""Look up an installed voice by name, case-insensitively."""
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for voice_name, language in available_voices():
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if voice_name.lower() == name.lower():
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return voice_name, language
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return None
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class AppleTTSService(TTSService):
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"""Speak text with a macOS system voice.
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Args:
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voice: An installed system voice name, e.g. "Moira" for Irish English.
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rate_wpm: Speaking rate in words per minute. None uses the voice default.
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"""
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def __init__(self, *, voice: str = "Moira", rate_wpm: int | None = None, **kwargs):
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super().__init__(
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push_start_frame=True,
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push_stop_frames=True,
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settings=TTSSettings(model=None, voice=voice, language=None),
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**kwargs,
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)
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self._voice = voice
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self._rate_wpm = rate_wpm
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self._resampler = create_stream_resampler()
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if find_voice(voice) is None:
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names = ", ".join(sorted(n for n, _ in available_voices())[:8])
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raise ValueError(
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f"macOS has no voice named {voice!r}. Installed voices include: {names}… "
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"Add more under System Settings > Accessibility > Spoken Content > System Voice."
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)
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def can_generate_metrics(self) -> bool:
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return True
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async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]:
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"""Synthesize one chunk of text."""
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await self.start_tts_usage_metrics(text)
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
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path = f.name
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try:
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command = [SAY, "-v", self._voice, "-o", path]
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if self._rate_wpm:
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command += ["-r", str(self._rate_wpm)]
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command += [f"--data-format=LEI16@{self.sample_rate}", "--", text]
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process = await asyncio.create_subprocess_exec(
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*command,
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stdout=asyncio.subprocess.DEVNULL,
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stderr=asyncio.subprocess.PIPE,
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)
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_, stderr = await process.communicate()
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if process.returncode != 0:
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detail = stderr.decode(errors="replace").strip()
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yield ErrorFrame(error=f"say failed ({process.returncode}): {detail}")
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return
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with wave.open(path, "rb") as wav:
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source_rate = wav.getframerate()
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while chunk := wav.readframes(_CHUNK_FRAMES):
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await self.stop_ttfb_metrics()
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if source_rate != self.sample_rate:
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chunk = await self._resampler.resample(
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chunk, source_rate, self.sample_rate
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)
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yield TTSAudioRawFrame(
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audio=chunk,
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sample_rate=self.sample_rate,
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num_channels=1,
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context_id=context_id,
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)
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except Exception as e:
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logger.exception(f"Apple TTS failed: {e}")
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yield ErrorFrame(error=f"Apple TTS failed: {e}")
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finally:
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await self.stop_ttfb_metrics()
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if os.path.exists(path):
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os.unlink(path)
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