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Running
on
Zero
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): | |
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, volume: float, pitch: float, sr: int | |
) -> 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") | |