python/FunASR-XL.git

			@@ -38,7 +38,6 @@
			from funasr.utils import asr_utils, wav_utils, postprocess_utils
			from funasr.models.frontend.wav_frontend import WavFrontend
			from funasr.tasks.vad import VADTask
			from funasr.utils.timestamp_tools import time_stamp_lfr6
			from funasr.bin.punctuation_infer import Text2Punc
			from funasr.bin.asr_inference_paraformer_vad_punc import Speech2Text
			from funasr.bin.asr_inference_paraformer_vad_punc import Speech2VadSegment
			@@ -168,6 +167,11 @@
			level=log_level,
			format="%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s",
			)

			if param_dict is not None:
			hotword_list_or_file = param_dict.get('hotword')
			else:
			hotword_list_or_file = None

			if ngpu >= 1 and torch.cuda.is_available():
			device = "cuda"
			@@ -207,6 +211,7 @@
			ngram_weight=ngram_weight,
			penalty=penalty,
			nbest=nbest,
			hotword_list_or_file=hotword_list_or_file,
			)
			speech2text = Speech2Text(**speech2text_kwargs)
			text2punc = None
			@@ -223,7 +228,19 @@
			output_dir_v2: Optional[str] = None,
			fs: dict = None,
			param_dict: dict = None,
			**kwargs,
			):

			hotword_list_or_file = None
			if param_dict is not None:
			hotword_list_or_file = param_dict.get('hotword')

			if 'hotword' in kwargs:
			hotword_list_or_file = kwargs['hotword']

			if speech2text.hotword_list is None:
			speech2text.hotword_list = speech2text.generate_hotwords_list(hotword_list_or_file)

			# 3. Build data-iterator
			if data_path_and_name_and_type is None and raw_inputs is not None:
			if isinstance(raw_inputs, torch.Tensor):
			@@ -241,6 +258,11 @@
			allow_variable_data_keys=allow_variable_data_keys,
			inference=True,
			)

			if param_dict is not None:
			use_timestamp = param_dict.get('use_timestamp', True)
			else:
			use_timestamp = True

			finish_count = 0
			file_count = 1
			@@ -284,8 +306,10 @@
			text, token, token_int = result[0], result[1], result[2]
			time_stamp = None if len(result) < 4 else result[3]


			postprocessed_result = postprocess_utils.sentence_postprocess(token, time_stamp)
			if use_timestamp and time_stamp is not None:
			postprocessed_result = postprocess_utils.sentence_postprocess(token, time_stamp)
			else:
			postprocessed_result = postprocess_utils.sentence_postprocess(token)
			text_postprocessed = ""
			time_stamp_postprocessed = ""
			text_postprocessed_punc = postprocessed_result
			@@ -293,9 +317,11 @@
			text_postprocessed, time_stamp_postprocessed, word_lists = postprocessed_result[0], \
			postprocessed_result[1], \
			postprocessed_result[2]
			text_postprocessed_punc = text_postprocessed
			if len(word_lists) > 0 and text2punc is not None:
			text_postprocessed_punc, punc_id_list = text2punc(word_lists, 20)
			else:
			text_postprocessed, word_lists = postprocessed_result[0], postprocessed_result[1]
			text_postprocessed_punc = text_postprocessed
			if len(word_lists) > 0 and text2punc is not None:
			text_postprocessed_punc, punc_id_list = text2punc(word_lists, 20)


			item = {'key': key, 'value': text_postprocessed_punc}
			@@ -312,7 +338,7 @@
			ibest_writer["token"][key] = " ".join(token)
			ibest_writer["token_int"][key] = " ".join(map(str, token_int))
			ibest_writer["vad"][key] = "{}".format(vadsegments)
			ibest_writer["text"][key] = text_postprocessed
			ibest_writer["text"][key] = " ".join(word_lists)
			ibest_writer["text_with_punc"][key] = text_postprocessed_punc
			if time_stamp_postprocessed is not None:
			ibest_writer["time_stamp"][key] = "{}".format(time_stamp_postprocessed)