lib/models/mac/whisper.py

from pywhispercpp.model import Model
import soundfile
import numpy as np
from logging import getLogger
from pathlib import Path

from lib.utils import Timer, read_audio

logger = getLogger(__name__)

MODEL_DIR = Path("/Users/jeqin/work/code/Translator/python_server/moyoyo_asr_models")
WHISPER_PROMPT_ZH = "以下是简体中文普通话的句子。"
WHISPER_PROMPT_EN = ""  # "The following is an English sentence."

class WhisperCPP:
    def __init__(self, model_dir=MODEL_DIR, source_lange: str = 'en') -> None:
        whisper_model = 'large-v3-turbo-q5_0'
        with Timer("load whisper"):
            self.model = Model(
                model=whisper_model,
                models_dir=str(model_dir),
                print_realtime=False,
                print_progress=False,
                print_timestamps=False,
                translate=False,
                # beam_search=1,
                temperature=0.,
                no_context=True
            )
        self._warmup()

    def _warmup(self):
        fake_audio = np.random.randn(16000).astype(np.float32)
        self.model.transcribe(fake_audio, print_progress=False)

    @staticmethod
    def config_language(language):
        if language == "zh":
            return WHISPER_PROMPT_ZH
        elif language == "en":
            return WHISPER_PROMPT_EN
        raise ValueError(f"Unsupported language : {language}")

    def transcribe(self, audio: np.ndarray, language):
        prompt = self.config_language(language)
        try:
            with Timer("whisper inference") as t:
                segments = self.model.transcribe(
                    audio,
                    initial_prompt=prompt,
                    language=language,
                    # token_timestamps=True,
                    split_on_word=True,
                    # max_len=max_len
                )
                text = "".join([s.text for s in segments])
            return text, t.duration
        except Exception as e:
            logger.error(e)
            return []

if __name__ == '__main__':
    from lib.utils import read_audio
    whisper = WhisperCPP()
    audio = read_audio(Path("/Users/jeqin/work/code/TestTranslator/test_data/recordings/1.wav"))
    text, time_cost = whisper.transcribe(audio, "zh")
    print(text)
    print(time_cost)