#!/usr/bin/env python3
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# -*- encoding: utf-8 -*-
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# Copyright FunASR (https://github.com/FunAudioLLM/SenseVoice). All Rights Reserved.
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# MIT License (https://opensource.org/licenses/MIT)
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import os
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import torch
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from pathlib import Path
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from funasr import AutoModel
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from funasr_torch import SenseVoiceSmallTorchScript as SenseVoiceSmall
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from funasr.utils.postprocess_utils import rich_transcription_postprocess
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model_dir = "iic/SenseVoiceSmall"
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model = AutoModel(
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model=model_dir,
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device="cuda:0",
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)
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# res = model.export(type="torchscript", quantize=False)
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# export model init
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model_path = "{}/.cache/modelscope/hub/{}".format(Path.home(), model_dir)
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model_bin = SenseVoiceSmall(model_path)
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# build tokenizer
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try:
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from funasr.tokenizer.sentencepiece_tokenizer import SentencepiecesTokenizer
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tokenizer = SentencepiecesTokenizer(bpemodel=os.path.join(model_path, "chn_jpn_yue_eng_ko_spectok.bpe.model"))
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except:
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tokenizer = None
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# inference
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wav_or_scp = "/Users/shixian/Downloads/asr_example_hotword.wav"
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language_list = [0]
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textnorm_list = [15]
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res = model_bin(wav_or_scp, language_list, textnorm_list, tokenizer=tokenizer)
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print([rich_transcription_postprocess(i) for i in res])
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