def load_directory(self, directory_path, condition):
filenames = [
filename for filename in os.listdir(directory_path)
if filename.endswith('.wav')
]
speakers = []
file_paths = []
speech_onset_offset_indices = []
regain_factors = []
sequences = []
for filename in filenames:
speaker_name = filename[0:4]
speakers.append(speaker_name)
filepath = os.path.join(directory_path, filename)
if condition == 'clean':
sequence = util.load_wav(filepath, self.sample_rate)
sequences.append(sequence)
self.num_sequences_in_memory += 1
regain_factors.append(self.regain / util.rms(sequence))
#如果extract_voice为true，则需要进行去除前后静音操作
if self.extract_voice:
#speech_onset_offset_indices是非静音段的起止点
speech_onset_offset_indices.append(
util.get_subsequence_with_speech_indices(sequence))
else:
if self.in_memory_percentage == 1 or np.random.uniform(
0, 1) <= (self.in_memory_percentage - 0.5) * 2:
sequence = util.load_wav(filepath, self.sample_rate)
sequences.append(sequence)
self.num_sequences_in_memory += 1
else:
sequences.append([-1])
if speaker_name not in self.speaker_mapping:
self.speaker_mapping[speaker_name] = len(
self.speaker_mapping) + 1
file_paths.append(filepath)
return sequences, file_paths, speakers, speech_onset_offset_indices, regain_factors
def load_directory(self, filenames, spk):
speakers = []
file_paths = []
speech_onset_offset_indices = []
regain_factors = []
sequences = []
for filename in filenames:
speaker_name = filename.split('/')[-1].split('_')[0][:3] if spk=='a' else \
filename.split('/')[-1].split('_')[2][:3]
speakers.append(speaker_name)
sequence = util.load_wav(filename, self.sample_rate)
sequences.append(sequence)
self.num_sequences_in_memory += 1
# regain_factors.append(self.regain / util.rms(sequence))
if self.extract_voice:
# get sub-sequence without front and ending silence
speech_onset_offset_indices.append(util.get_subsequence_with_speech_indices(sequence))
if speaker_name not in self.speaker_mapping:
self.speaker_mapping[speaker_name] = len(self.speaker_mapping) + 1
return sequences, speakers, speech_onset_offset_indices, regain_factors