#!/usr/bin/env python3 # -*- encoding: utf-8 -*- # Copyright FunASR (https://github.com/alibaba-damo-academy/FunClip). All Rights Reserved. # MIT License (https://opensource.org/licenses/MIT) import os import re import numpy as np PUNC_LIST = [',', '。', '!', '?', '、'] def pre_proc(text): res = '' for i in range(len(text)): if text[i] in PUNC_LIST: continue if '\u4e00' <= text[i] <= '\u9fff': if len(res) and res[-1] != " ": res += ' ' + text[i]+' ' else: res += text[i]+' ' else: res += text[i] if res[-1] == ' ': res = res[:-1] return res def proc(raw_text, timestamp, dest_text): # simple matching ld = len(dest_text.split()) mi, ts = [], [] offset = 0 while True: fi = raw_text.find(dest_text, offset, len(raw_text)) ti = raw_text[:fi].count(' ') if fi == -1: break offset = fi + ld mi.append(fi) ts.append([timestamp[ti][0]*16, timestamp[ti+ld-1][1]*16]) return ts def proc_spk(dest_spk, sd_sentences): ts = [] for d in sd_sentences: d_start = d['timestamp'][0][0] d_end = d['timestamp'][-1][1] spkid=dest_spk[3:] if str(d['spk']) == spkid and d_end-d_start>999: ts.append([d['start']*16, d['end']*16]) return ts def generate_vad_data(data, sd_sentences, sr=16000): assert len(data.shape) == 1 vad_data = [] for d in sd_sentences: d_start = round(d['ts_list'][0][0]/1000, 2) d_end = round(d['ts_list'][-1][1]/1000, 2) vad_data.append([d_start, d_end, data[int(d_start * sr):int(d_end * sr)]]) return vad_data def write_state(output_dir, state): for key in ['/recog_res_raw', '/timestamp', '/sentences']:#, '/sd_sentences']: with open(output_dir+key, 'w') as fout: fout.write(str(state[key[1:]])) if 'sd_sentences' in state: with open(output_dir+'/sd_sentences', 'w') as fout: fout.write(str(state['sd_sentences'])) def load_state(output_dir): state = {} with open(output_dir+'/recog_res_raw') as fin: line = fin.read() state['recog_res_raw'] = line with open(output_dir+'/timestamp') as fin: line = fin.read() state['timestamp'] = eval(line) with open(output_dir+'/sentences') as fin: line = fin.read() state['sentences'] = eval(line) if os.path.exists(output_dir+'/sd_sentences'): with open(output_dir+'/sd_sentences') as fin: line = fin.read() state['sd_sentences'] = eval(line) return state def convert_pcm_to_float(data): if data.dtype == np.float64: return data elif data.dtype == np.float32: return data.astype(np.float64) elif data.dtype == np.int16: bit_depth = 16 elif data.dtype == np.int32: bit_depth = 32 elif data.dtype == np.int8: bit_depth = 8 else: raise ValueError("Unsupported audio data type") # Now handle the integer types max_int_value = float(2 ** (bit_depth - 1)) if bit_depth == 8: data = data - 128 return (data.astype(np.float64) / max_int_value) def convert_time_to_millis(time_str): # 格式: [小时:分钟:秒,毫秒] hours, minutes, seconds, milliseconds = map(int, re.split('[:,]', time_str)) return (hours * 3600 + minutes * 60 + seconds) * 1000 + milliseconds def extract_timestamps(input_text): # 使用正则表达式查找所有时间戳 timestamps = re.findall(r'\[(\d{2}:\d{2}:\d{2},\d{2,3})\s*-\s*(\d{2}:\d{2}:\d{2},\d{2,3})\]', input_text) times_list = [] print(timestamps) # 循环遍历找到的所有时间戳,并转换为毫秒 for start_time, end_time in timestamps: start_millis = convert_time_to_millis(start_time) end_millis = convert_time_to_millis(end_time) times_list.append([start_millis, end_millis]) return times_list if __name__ == '__main__': text = ("1. [00:00:00,500-00:00:05,850] 在我们的设计普惠当中,有一个我经常津津乐道的项目叫寻找远方的美好。" "2. [00:00:07,120-00:00:12,940] 啊,在这样一个我们叫寻美在这样的一个项目当中,我们把它跟乡村振兴去结合起来,利用我们的设计的能力。" "3. [00:00:13,240-00:00:25,620] 问我们自身员工的设设计能力,我们设计生态伙伴的能力,帮助乡村振兴当中,要希望把他的产品推向市场,把他的农产品把他加工产品推向市场的这样的伙伴做一件事情,") print(extract_timestamps(text))