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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, 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")
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