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import librosa
import torch as th
import numpy as np
import soundfile as sf
import sys, os
sys.path.append(os.path.dirname(__file__))
# from speex_linear.lp_or_tde import LP_or_TDE
def audio(path, fs=16000):
wave_data, sr = sf.read(path)
if sr != fs:
wave_data = librosa.resample(wave_data, orig_sr=sr, target_sr=fs)
return wave_data
def get_firstchannel_read(path, fs=16000):
wave_data, sr = sf.read(path)
if sr != fs:
if len(wave_data.shape) != 1:
wave_data = wave_data.transpose((1, 0))
wave_data = librosa.resample(wave_data, orig_sr=sr, target_sr=fs)
if len(wave_data.shape) != 1:
wave_data = wave_data.transpose((1, 0))
if len(wave_data.shape) > 1:
wave_data = wave_data[:, 0]
return wave_data
def parse_scp(scp, path_list):
with open(scp) as fid:
for line in fid:
tmp = line.strip().split()
if len(tmp) > 1:
path_list.append({"inputs": tmp[0], "duration": tmp[1]})
else:
path_list.append({"inputs": tmp[0]})
class DataReaderAEC(object):
def __init__(self, filename, sample_rate): #, aux_segment): # filename是不带id的待解码音频，noisy_id是带id的带解码音频，clean是带id的注册音频
self.file_list = []
parse_scp(filename, self.file_list)
self.sample_rate = sample_rate
# self.aux_segment_length = aux_segment * sample_rate
def extract_feature(self, path):
mic_path = path["inputs"]
utt_id = mic_path.split("/")[-1]
mic_name = mic_path.split("/")[-1].split(".")[0]
ref_path = mic_path.replace("mic.wav", "lpb.wav")
ref_name = ref_path.split("/")[-1].split(".")[0]
mic = get_firstchannel_read(mic_path, self.sample_rate).astype(np.float32)
ref = get_firstchannel_read(ref_path, self.sample_rate).astype(np.float32)
min_len = min(mic.shape[0], ref.shape[0])
mic = mic[:min_len]
ref = ref[:min_len]
inputs_mic = np.reshape(mic, [1, mic.shape[0]])
inputs_ref = np.reshape(ref, [1, ref.shape[0]]).astype(np.float32)
inputs_mic = th.from_numpy(inputs_mic)
inputs_ref = th.from_numpy(inputs_ref)
# print(f'e: {inputs_e.shape}')
# print(f'mic: {inputs_mic.shape}')
# print(f'ref: {inputs_ref.shape}')
egs = {
"mic": inputs_mic,
"ref": inputs_ref,
"utt_id": utt_id,
"mic_name": mic_name,
"ref_name": ref_name
# "max_norm": max_norm
}
return egs
def __len__(self):
return len(self.file_list)
def __getitem__(self, index):
return self.extract_feature(self.file_list[index])
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