TimeStretch

class audioflux.TimeStretch(radix2_exp=12, slide_length=1024, window_type=WindowType.HANN)

Time stretch algorithm

Parameters
radix2_exp: int

fft_length=2**radix2_exp

slide_length: int

Window sliding length.

window_type: WindowType

Window type for each frame.

See: type.WindowType

Examples

Read voice audio data

>>> import audioflux as af
>>> audio_path = af.utils.sample_path('voice')
>>> audio_arr, sr = af.read(audio_path)

Compute the time stretch

>>> time_stretch_obj = af.TimeStretch(radix2_exp=12, window_type=af.type.WindowType.HANN, slide_length=1024)
>>> new_audio_arr = time_stretch_obj.time_stretch(audio_arr, 0.5)
>>> # af.write('./audio_arr_0_5.wav', new_audio_arr, sr)

Show plot

>>> import matplotlib.pyplot as plt
>>> fig, axes = plt.subplots(nrows=2, sharex=True)
>>> ax = af.display.fill_wave(audio_arr, sr, axes=axes[0])
>>> ax.set_title('Original')
>>> ax = af.display.fill_wave(new_audio_arr, sr, axes=axes[1])
>>> ax.set_title('0.5x TimeStretch')
../_images/timeStretch-1.png

Methods

cal_data_capacity(rate, data_length)

Calculate the data capacity.

time_stretch(data_arr, rate)

Compute the time stretch
cal_data_capacity(rate, data_length)

Calculate the data capacity.

Parameters
rate: float

Time stretch rate

data_length: int

Input array length

Returns
out: int
time_stretch(data_arr, rate)

Compute the time stretch

Parameters
data_arr: np.ndarray [shape=(…, n)]

Audio data array

rate: float

Time stretch rate

Returns
arr: np.ndarray [shape=(…, n1)]