| | |
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| | | from funasr.utils.types import str2triple_str |
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| | | from funasr.utils.types import str_or_none |
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| | | from funasr.utils.vad_utils import slice_padding_fbank |
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| | | |
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| | | from tqdm import tqdm |
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| | | |
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| | | def inference_asr( |
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| | | maxlenratio: float, |
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| | |
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| | | |
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| | | batch_size_token_ms_cum = 0 |
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| | | beg_idx = 0 |
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| | | for j, _ in enumerate(range(0, n)): |
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| | | beg_asr_total = time.time() |
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| | | for j, _ in enumerate(tqdm(range(0, n))): |
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| | | batch_size_token_ms_cum += (sorted_data[j][0][1] - sorted_data[j][0][0]) |
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| | | if j < n - 1 and (batch_size_token_ms_cum + sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0]) < batch_size_token_ms and (sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0]) < batch_size_token_threshold_s: |
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| | | continue |
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| | |
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| | | beg_idx = end_idx |
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| | | batch = {"speech": speech_j, "speech_lengths": speech_lengths_j} |
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| | | batch = to_device(batch, device=device) |
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| | | print("batch: ", speech_j.shape[0]) |
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| | | # print("batch: ", speech_j.shape[0]) |
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| | | beg_asr = time.time() |
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| | | results = speech2text(**batch) |
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| | | end_asr = time.time() |
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| | | print("time cost asr: ", end_asr - beg_asr) |
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| | | # print("time cost asr: ", end_asr - beg_asr) |
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| | | |
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| | | if len(results) < 1: |
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| | | results = [["", [], [], [], [], [], []]] |
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| | | results_sorted.extend(results) |
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| | | |
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| | | end_asr_total = time.time() |
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| | | print("total time cost asr: ", end_asr_total-beg_asr_total) |
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| | | restored_data = [0] * n |
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| | | for j in range(n): |
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| | | index = sorted_data[j][1] |
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| | |
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| | | quantize_modules: Optional[List[str]] = None, |
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| | | quantize_dtype: Optional[str] = "float16", |
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| | | streaming: Optional[bool] = False, |
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| | | simu_streaming: Optional[bool] = False, |
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| | | fake_streaming: Optional[bool] = False, |
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| | | full_utt: Optional[bool] = False, |
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| | | chunk_size: Optional[int] = 16, |
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| | | left_context: Optional[int] = 16, |
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| | |
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| | | quantize_modules=quantize_modules, |
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| | | quantize_dtype=quantize_dtype, |
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| | | streaming=streaming, |
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| | | simu_streaming=simu_streaming, |
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| | | fake_streaming=fake_streaming, |
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| | | full_utt=full_utt, |
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| | | chunk_size=chunk_size, |
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| | | left_context=left_context, |
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| | |
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| | | final_hyps = speech2text.streaming_decode( |
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| | | speech[_end: len(speech)], is_final=True |
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| | | ) |
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| | | elif speech2text.simu_streaming: |
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| | | final_hyps = speech2text.simu_streaming_decode(**batch) |
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| | | elif speech2text.fake_streaming: |
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| | | final_hyps = speech2text.fake_streaming_decode(**batch) |
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| | | elif speech2text.full_utt: |
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| | | final_hyps = speech2text.full_utt_decode(**batch) |
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| | | else: |
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| | |
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| | | group.add_argument("--lm_weight", type=float, default=1.0, help="RNNLM weight") |
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| | | group.add_argument("--ngram_weight", type=float, default=0.9, help="ngram weight") |
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| | | group.add_argument("--streaming", type=str2bool, default=False) |
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| | | group.add_argument("--simu_streaming", type=str2bool, default=False) |
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| | | group.add_argument("--fake_streaming", type=str2bool, default=False) |
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| | | group.add_argument("--full_utt", type=str2bool, default=False) |
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| | | group.add_argument("--chunk_size", type=int, default=16) |
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| | | group.add_argument("--left_context", type=int, default=16) |
|---|
