oband

class diffsptk.FractionalOctaveBandAnalysis(sample_rate: int, *, f_min: float = 40, f_ref: float = 1000, f_max: float = 8000, filter_order: int = 1000, n_fract: int = 1, overlap: float = 1)

Fractional octave filter band analysis module.

Parameters:

sample_rateint >= 1

The sample rate in Hz.

f_minfloat >= 0

The minimum frequency in Hz.

f_reffloat >= 0

The reference frequency in Hz.

f_maxfloat <= sample_rate // 2

The maximum frequency in Hz.

filter_orderint >= 3

The order of the filter.

n_fractint >= 1

The number of fractions.

overlapfloat in [0, 1]

The overlap factor.

References

[1]

J. Antoni, “Orthogonal-like fractional-octave-band filters,” The Journal of the Acoustical Society of America, vol. 127, no. 2, pp. 884-895, 2010.

forward(x: Tensor) → Tensor

Perform fractional octave filter band analysis.

Parameters:

xTensor [shape=(B, 1, T) or (B, T) or (T,)]

The input signal.

Returns:

outTensor [shape=(B, K, T)]

The analyzed signal.

Examples

>>> x = diffsptk.ramp(0, 1, 0.25)
>>> x
tensor([0.0000, 0.2500, 0.5000, 0.7500, 1.0000])
>>> oband = diffsptk.FractionalOctaveBandAnalysis(16000)
>>> y = oband(x)
>>> y.shape
torch.Size([1, 9, 5])
>>> y.sum(1).squeeze()
tensor([-0.0184,  0.0969,  0.3940,  0.6062,  0.9033])

See also

pqmf gammatone