import sys from pydub import AudioSegment import soundfile as sf import pyrubberband as pyrb import numpy as np from io import BytesIO INT16_MAX = np.iinfo(np.int16).max def audio_to_int16(audio_data): if ( audio_data.dtype == np.float32 or audio_data.dtype == np.float64 or audio_data.dtype == np.float128 or audio_data.dtype == np.float16 ): audio_data = (audio_data * INT16_MAX).astype(np.int16) return audio_data def audiosegment_to_librosawav(audiosegment: AudioSegment) -> np.ndarray: """ Converts pydub audio segment into np.float32 of shape [duration_in_seconds*sample_rate, channels], where each value is in range [-1.0, 1.0]. """ channel_sounds = audiosegment.split_to_mono() samples = [s.get_array_of_samples() for s in channel_sounds] fp_arr = np.array(samples).T.astype(np.float32) fp_arr /= np.iinfo(samples[0].typecode).max fp_arr = fp_arr.reshape(-1) return fp_arr def pydub_to_np(audio: AudioSegment) -> tuple[int, np.ndarray]: """ Converts pydub audio segment into np.float32 of shape [duration_in_seconds*sample_rate, channels], where each value is in range [-1.0, 1.0]. Returns tuple (audio_np_array, sample_rate). """ return ( audio.frame_rate, np.array(audio.get_array_of_samples(), dtype=np.float32).reshape( (-1, audio.channels) ) / (1 << (8 * audio.sample_width - 1)), ) def ndarray_to_segment(ndarray, frame_rate): buffer = BytesIO() sf.write(buffer, ndarray, frame_rate, format="wav") buffer.seek(0) sound = AudioSegment.from_wav( buffer, ) return sound def time_stretch(input_segment: AudioSegment, time_factor: float) -> AudioSegment: """ factor range -> [0.2,10] """ time_factor = np.clip(time_factor, 0.2, 10) sr = input_segment.frame_rate y = audiosegment_to_librosawav(input_segment) y_stretch = pyrb.time_stretch(y, sr, time_factor) sound = ndarray_to_segment( y_stretch, frame_rate=sr, ) return sound def pitch_shift( input_segment: AudioSegment, pitch_shift_factor: float, ) -> AudioSegment: """ factor range -> [-12,12] """ pitch_shift_factor = np.clip(pitch_shift_factor, -12, 12) sr = input_segment.frame_rate y = audiosegment_to_librosawav(input_segment) y_shift = pyrb.pitch_shift(y, sr, pitch_shift_factor) sound = ndarray_to_segment( y_shift, frame_rate=sr, ) return sound def apply_prosody_to_audio_data( audio_data: np.ndarray, rate: float = 1, volume: float = 0, pitch: float = 0, sr: int = 24000, ) -> np.ndarray: if rate != 1: audio_data = pyrb.time_stretch(audio_data, sr=sr, rate=rate) if volume != 0: audio_data = audio_data * volume if pitch != 0: audio_data = pyrb.pitch_shift(audio_data, sr=sr, n_steps=pitch) return audio_data if __name__ == "__main__": input_file = sys.argv[1] time_stretch_factors = [0.5, 0.75, 1.5, 1.0] pitch_shift_factors = [-12, -5, 0, 5, 12] input_sound = AudioSegment.from_mp3(input_file) for time_factor in time_stretch_factors: output_wav = f"time_stretched_{int(time_factor * 100)}.wav" sound = time_stretch(input_sound, time_factor) sound.export(output_wav, format="wav") for pitch_factor in pitch_shift_factors: output_wav = f"pitch_shifted_{int(pitch_factor * 100)}.wav" sound = pitch_shift(input_sound, pitch_factor) sound.export(output_wav, format="wav")