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| | | from funasr.download.file import download_from_url |
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| | | from funasr.utils.timestamp_tools import timestamp_sentence |
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| | | from funasr.utils.timestamp_tools import timestamp_sentence_en |
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| | | from funasr.download.download_from_hub import download_model |
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| | | from funasr.download.download_model_from_hub import download_model |
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| | | from funasr.utils.vad_utils import slice_padding_audio_samples |
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| | | from funasr.utils.vad_utils import merge_vad |
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| | | from funasr.utils.load_utils import load_audio_text_image_video |
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| | |
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| | | speed_stats["rtf"] = f"{(time_escape) / batch_data_time:0.3f}" |
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| | | description = f"{speed_stats}, " |
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| | | if pbar: |
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| | | pbar.update(1) |
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| | | pbar.update(end_idx - beg_idx) |
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| | | pbar.set_description(description) |
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| | | time_speech_total += batch_data_time |
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| | | time_escape_total += time_escape |
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| | |
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| | | # FIX(gcf): concat the vad clips for sense vocie model for better aed |
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| | | if kwargs.get("merge_vad", False): |
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| | | for i in range(len(res)): |
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| | | res[i]["value"] = merge_vad(res[i]["value"], kwargs.get("merge_length", 15000)) |
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| | | res[i]["value"] = merge_vad( |
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| | | res[i]["value"], kwargs.get("merge_length_s", 15) * 1000 |
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| | | ) |
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| | | |
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| | | # step.2 compute asr model |
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| | | model = self.model |
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| | |
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| | | |
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| | | if len(sorted_data) > 0 and len(sorted_data[0]) > 0: |
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| | | batch_size = max(batch_size, sorted_data[0][0][1] - sorted_data[0][0][0]) |
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| | | |
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| | | if kwargs["device"] == "cpu": |
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| | | batch_size = 0 |
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| | | |
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| | | beg_idx = 0 |
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| | | beg_asr_total = time.time() |
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| | |
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| | | sv_output = postprocess(all_segments, None, labels, spk_embedding.cpu()) |
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| | | if self.spk_mode == "vad_segment": # recover sentence_list |
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| | | sentence_list = [] |
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| | | for res, vadsegment in zip(restored_data, vadsegments): |
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| | | if "timestamp" not in res: |
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| | | for rest, vadsegment in zip(restored_data, vadsegments): |
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| | | if "timestamp" not in rest: |
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| | | logging.error( |
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| | | "Only 'iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch' \ |
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| | | and 'iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'\ |
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| | |
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| | | { |
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| | | "start": vadsegment[0], |
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| | | "end": vadsegment[1], |
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| | | "sentence": res["text"], |
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| | | "timestamp": res["timestamp"], |
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| | | "sentence": rest["text"], |
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| | | "timestamp": rest["timestamp"], |
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| | | } |
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| | | ) |
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| | | elif self.spk_mode == "punc_segment": |
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