Rename 'res' in line 514 to avoid with naming conflict with line 365

liugz18

2024-07-18 d80ac2fd2df4e7fb8a28acfa512bb11472b5cc99

 funasr/utils/vad_utils.py

@@ -1,18 +1,55 @@
import torch
from torch.nn.utils.rnn import pad_sequence


def slice_padding_fbank(speech, speech_lengths, vad_segments):
   speech_list = []
   speech_lengths_list = []
   for i, segment in enumerate(vad_segments):
		
      bed_idx = int(segment[0][0]*16)
      end_idx = min(int(segment[0][1]*16), speech_lengths[0])
      speech_i = speech[0, bed_idx: end_idx]
      speech_lengths_i = end_idx-bed_idx
      speech_list.append(speech_i)
      speech_lengths_list.append(speech_lengths_i)
   feats_pad = pad_sequence(speech_list, batch_first=True, padding_value=0.0)
   speech_lengths_pad = torch.Tensor(speech_lengths_list).int()
   return feats_pad, speech_lengths_pad
	
    speech_list = []
    speech_lengths_list = []
    for i, segment in enumerate(vad_segments):

        bed_idx = int(segment[0][0] * 16)
        end_idx = min(int(segment[0][1] * 16), speech_lengths[0])
        speech_i = speech[0, bed_idx:end_idx]
        speech_lengths_i = end_idx - bed_idx
        speech_list.append(speech_i)
        speech_lengths_list.append(speech_lengths_i)
    feats_pad = pad_sequence(speech_list, batch_first=True, padding_value=0.0)
    speech_lengths_pad = torch.Tensor(speech_lengths_list).int()
    return feats_pad, speech_lengths_pad


def slice_padding_audio_samples(speech, speech_lengths, vad_segments):
    speech_list = []
    speech_lengths_list = []
    for i, segment in enumerate(vad_segments):
        bed_idx = int(segment[0][0] * 16)
        end_idx = min(int(segment[0][1] * 16), speech_lengths)
        speech_i = speech[bed_idx:end_idx]
        speech_lengths_i = end_idx - bed_idx
        speech_list.append(speech_i)
        speech_lengths_list.append(speech_lengths_i)

    return speech_list, speech_lengths_list


def merge_vad(vad_result, max_length=15000):
    new_result = []
    time_step = [t[0] for t in vad_result] + [t[1] for t in vad_result]
    time_step = sorted(list(set(time_step)))
    if len(time_step) == 0:
        return []
    bg = 0
    for i in range(len(time_step) - 1):
        time = time_step[i]
        if time_step[i + 1] - bg < max_length:
            continue
        if time - bg < max_length * 1.5:
            new_result.append([bg, time])
        else:
            split_num = int(time - bg) // max_length + 1
            spl_l = int(time - bg) // split_num
            for j in range(split_num):
                new_result.append([bg + j * spl_l, bg + (j + 1) * spl_l])
        bg = time
    new_result.append([bg, time_step[-1]])
    return new_result