| | |
| | | if data_type == "kaldi_ark": |
| | | ark_reader = ReadHelper('ark:{}'.format(data_file)) |
| | | reader_list.append(ark_reader) |
| | | elif data_type == "text" or data_type == "sound": |
| | | elif data_type == "text" or data_type == "sound" or data_type == 'text_hotword': |
| | | text_reader = open(data_file, "r") |
| | | reader_list.append(text_reader) |
| | | elif data_type == "none": |
| | |
| | | sample_dict["sampling_rate"] = sampling_rate |
| | | if data_name == "speech": |
| | | sample_dict["key"] = key |
| | | elif data_type == "text_hotword": |
| | | text = item |
| | | segs = text.strip().split() |
| | | sample_dict[data_name] = segs[1:] |
| | | if "key" not in sample_dict: |
| | | sample_dict["key"] = segs[0] |
| | | sample_dict['hw_tag'] = 1 |
| | | else: |
| | | text = item |
| | | segs = text.strip().split() |
| | |
| | | shuffle = conf.get('shuffle', True) |
| | | data_names = conf.get("data_names", "speech,text") |
| | | data_types = conf.get("data_types", "kaldi_ark,text") |
| | | dataset = AudioDataset(scp_lists, data_names, data_types, frontend_conf=frontend_conf, shuffle=shuffle, mode=mode) |
| | | |
| | | pre_hwfile = conf.get("pre_hwlist", None) |
| | | pre_prob = conf.get("pre_prob", 0) # unused yet |
| | | |
| | | hw_config = {"sample_rate": conf.get("sample_rate", 0.6), |
| | | "double_rate": conf.get("double_rate", 0.1), |
| | | "hotword_min_length": conf.get("hotword_min_length", 2), |
| | | "hotword_max_length": conf.get("hotword_max_length", 8), |
| | | "pre_prob": conf.get("pre_prob", 0.0)} |
| | | |
| | | if pre_hwfile is not None: |
| | | pre_hwlist = [] |
| | | with open(pre_hwfile, 'r') as fin: |
| | | for line in fin.readlines(): |
| | | pre_hwlist.append(line.strip()) |
| | | else: |
| | | pre_hwlist = None |
| | | |
| | | dataset = AudioDataset(scp_lists, |
| | | data_names, |
| | | data_types, |
| | | frontend_conf=frontend_conf, |
| | | shuffle=shuffle, |
| | | mode=mode, |
| | | ) |
| | | |
| | | filter_conf = conf.get('filter_conf', {}) |
| | | filter_fn = partial(filter, **filter_conf) |
| | | dataset = FilterIterDataPipe(dataset, fn=filter_fn) |
| | | |
| | | if "text" in data_names: |
| | | vocab = {'vocab': dict, 'seg_dict': seg_dict, 'punc_dict': punc_dict, 'bpe_tokenizer': bpe_tokenizer} |
| | | vocab = {'vocab': dict, 'seg_dict': seg_dict, 'punc_dict': punc_dict, 'bpe_tokenizer': bpe_tokenizer, 'hw_config': hw_config} |
| | | tokenize_fn = partial(tokenize, **vocab) |
| | | dataset = MapperIterDataPipe(dataset, fn=tokenize_fn) |
| | | |