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import io |
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import wave |
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from dataclasses import dataclass |
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from typing import Literal, Optional, Tuple |
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import numpy as np |
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from fish_speech.text.chn_text_norm.text import Text as ChnNormedText |
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@dataclass |
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class InferenceResult: |
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code: Literal["header", "segment", "error", "final"] |
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audio: Optional[Tuple[int, np.ndarray]] |
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error: Optional[Exception] |
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def normalize_text(user_input: str, use_normalization: bool) -> str: |
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"""Normalize user input text if needed.""" |
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if use_normalization: |
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return ChnNormedText(raw_text=user_input).normalize() |
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else: |
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return user_input |
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def wav_chunk_header( |
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sample_rate: int = 44100, bit_depth: int = 16, channels: int = 1 |
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) -> bytes: |
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buffer = io.BytesIO() |
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with wave.open(buffer, "wb") as wav_file: |
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wav_file.setnchannels(channels) |
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wav_file.setsampwidth(bit_depth // 8) |
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wav_file.setframerate(sample_rate) |
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wav_header_bytes = buffer.getvalue() |
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buffer.close() |
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return wav_header_bytes |
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