def preprocess(self, x):
"""
By default, no pre-processing is applied to a microphone input file
"""
file_obj = processing_utils.decode_base64_to_file(x)
if self.preprocessing == "mfcc":
return processing_utils.generate_mfcc_features_from_audio_file(file_obj.name)
_, signal = scipy.io.wavfile.read(file_obj.name)
return signal
def embed(self, x):
"""
Resamples each audio signal to be 1,000 frames and then returns the flattened vectors
"""
num_frames = 1000
if self.type == "file":
filename = x.name
mfcc = processing_utils.generate_mfcc_features_from_audio_file(filename, downsample_to=num_frames)
return mfcc.flatten()
elif self.type == "numpy":
sample_rate, signal = x
mfcc = processing_utils.generate_mfcc_features_from_audio_file(wav_filename=None, sample_rate=sample_rate, signal=signal, downsample_to=num_frames)
return mfcc.flatten()
elif self.type == "mfcc":
mfcc = scipy.signal.resample(x, num_frames, axis=1)
return mfcc.flatten()
else:
raise ValueError("Unknown type: " + str(self.type) + ". Please choose from: 'numpy', 'mfcc', 'file'.")
