Run through a single audio file

def train_on_audio(self, fn: str):
        """Run through a single audio file"""
        save_test = random() > 0.8
        audio = load_audio(fn)
        num_chunks = len(audio) // self.args.chunk_size

        self.listener.clear()

        for i, chunk in enumerate(chunk_audio(audio, self.args.chunk_size)):
            print('\r' + str(i * 100. / num_chunks) + '%', end='', flush=True)
            self.audio_buffer = np.concatenate((self.audio_buffer[len(chunk):], chunk))
            conf = self.listener.update(chunk)
            if conf > self.args.threshold:
                self.samples_since_train += 1
                name = splitext(basename(fn))[0] + '-' + str(i) + '.wav'
                name = join(self.args.folder, 'test' if save_test else '', 'not-wake-word',
                            'generated', name)
                save_audio(name, self.audio_buffer)
                print()
                print('Saved to:', name)

            if not save_test and self.samples_since_train >= self.args.delay_samples and \
                    self.args.epochs > 0:
                self.samples_since_train = 0
                self.retrain()