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Update API Documentation / build-api-docs (push) Has been cancelled
Add complete FunASR codebase including models, runtime, and documentation.
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
import numpy as np
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import soundfile as sf
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import torch
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from model import FunASRNano
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from tools.utils import load_audio
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def main():
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model_dir = "FunAudioLLM/Fun-ASR-Nano-2512"
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device = (
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"cuda:0"
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if torch.cuda.is_available()
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else "mps" if torch.backends.mps.is_available() else "cpu"
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)
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m, kwargs = FunASRNano.from_pretrained(model=model_dir, device=device)
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tokenizer = kwargs.get("tokenizer", None)
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m.eval()
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wav_path = f"{kwargs['model_path']}/example/zh.mp3"
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res = m.inference(data_in=[wav_path], **kwargs)
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text = res[0][0]
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print(text)
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chunk_size = 0.72
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duration = sf.info(wav_path).duration
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cum_durations = np.arange(chunk_size, duration + chunk_size, chunk_size)
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prev_text = ""
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for idx, cum_duration in enumerate(cum_durations):
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audio, rate = load_audio(wav_path, 16000, duration=round(cum_duration, 3))
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prev_text = m.inference([torch.tensor(audio)], prev_text=prev_text, **kwargs)[0][0]["text"]
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if idx != len(cum_durations) - 1:
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prev_text = tokenizer.decode(tokenizer.encode(prev_text)[:-5]).replace("�", "")
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if prev_text:
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print(prev_text)
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if __name__ == "__main__":
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main()
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