speech_recognition/FunASR
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update egs_modelscope paraformer-large-en

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北念 2023-10-17 14:06:47 +08:00
parent 8a16e1c13e
commit fde48a8652
4 changed files with 12 additions and 4 deletions
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2
egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/infer.py
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@ -16,7 +16,7 @@ def modelscope_infer(args):
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--model', type=str, default="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch")
parser.add_argument('--model', type=str, default="damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020")
parser.add_argument('--audio_in', type=str, default="./data/test/wav.scp")
parser.add_argument('--output_dir', type=str, default="./results/")
parser.add_argument('--decoding_mode', type=str, default="normal")

2
egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/infer.sh
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@ -6,7 +6,7 @@ set -o pipefail
stage=1
stop_stage=2
model="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch"
model="damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020"
data_dir="./data/test"
output_dir="./results"
batch_size=64

8
funasr/bin/asr_infer.py
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@ -1918,6 +1918,8 @@ class Speech2TextWhisper:
nbest: int = 1,
streaming: bool = False,
frontend_conf: dict = None,
language: str = None,
task: str = "transcribe",
**kwargs,
):
@ -1960,6 +1962,8 @@ class Speech2TextWhisper:
self.device = device
self.dtype = dtype
self.frontend = frontend
self.language = language
self.task = task
@torch.no_grad()
def __call__(
@ -1986,10 +1990,10 @@ class Speech2TextWhisper:
mel = log_mel_spectrogram(speech).to(self.device)
if self.asr_model.is_multilingual:
options = DecodingOptions(fp16=False)
options = DecodingOptions(fp16=False, language=self.language, task=self.task)
asr_res = decode(self.asr_model, mel, options)
text = asr_res.text
language = asr_res.language
language = self.language if self.language else asr_res.language
else:
asr_res = transcribe(self.asr_model, speech, fp16=False)
text = asr_res["text"]

4
funasr/bin/asr_inference_launch.py
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@ -2056,6 +2056,8 @@ def inference_whisper(
ncpu = kwargs.get("ncpu", 1)
torch.set_num_threads(ncpu)
language = param_dict.get("language", None)
task = param_dict.get("task", "transcribe")
if batch_size > 1:
raise NotImplementedError("batch decoding is not implemented")
if word_lm_train_config is not None:
@ -2099,6 +2101,8 @@ def inference_whisper(
penalty=penalty,
nbest=nbest,
streaming=streaming,
language=language,
task=task,
)
logging.info("speech2text_kwargs: {}".format(speech2text_kwargs))
speech2text = Speech2TextWhisper(**speech2text_kwargs)