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69 lines
1.6 KiB
Python
69 lines
1.6 KiB
Python
"""
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Text-to-Speech module using Kokoro TTS.
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Handles loading and running the Kokoro text-to-speech model.
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"""
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import logging
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import re
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import sounddevice as sd
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import torch
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from kokoro import KPipeline
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logger = logging.getLogger(__name__)
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# Model configuration
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TTS_MODEL_NAME = "hexgrad/Kokoro-82M"
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# Device configuration
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DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
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# Emoji removal pattern
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EMOJI_PATTERN = re.compile(
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"["
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"\U0001F600-\U0001F64F" # emoticons
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"\U0001F300-\U0001F5FF" # symbols & pictographs
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"\U0001F680-\U0001F6FF" # transport & map symbols
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"\U0001F1E0-\U0001F1FF" # flags
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"\u2600-\u26FF" # misc symbols
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"\u2700-\u27BF" # dingbats
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"]+",
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flags=re.UNICODE,
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)
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# Create global pipeline (loads model once)
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logger.info(f"Loading {TTS_MODEL_NAME} on {DEVICE}...")
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kpipeline = KPipeline(
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repo_id=TTS_MODEL_NAME,
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lang_code="a", # "a" = auto
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device=DEVICE
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)
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def remove_emoji(text: str) -> str:
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"""Remove emoji characters from text."""
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return EMOJI_PATTERN.sub("", text)
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def speak_stream(text: str, voice: str = "af_bella", speed: float = 1.2):
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"""
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Generate speech from text using Kokoro and stream to speakers.
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Args:
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text: Text to synthesize
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voice: Voice model to use (default: af_bella)
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speed: Speech speed multiplier (default: 1.2)
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"""
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generator = kpipeline(
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text,
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voice=voice,
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speed=speed,
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split_pattern=r"\n+",
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)
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sample_rate = 24000 # Kokoro uses 24 kHz
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for _, _, audio in generator:
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sd.play(audio, samplerate=sample_rate, blocking=True)
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