chroma

class diffsptk.ChromaFilterBankAnalysis(*, fft_length: int, n_channel: int, sample_rate: int, norm: float = inf, use_power: bool = True)

Chroma filter bank analysis module.

Parameters:

fft_lengthint >= 2

The number of FFT bins, \(L\).

n_channelint >= 1

The number of chroma filter banks, \(C\).

sample_rateint >= 1

The sample rate in Hz.

normfloat

The normalization factor.

use_powerbool

If True, use the power spectrum instead of the amplitude spectrum.

forward(x: Tensor) → Tensor

Apply chroma filter banks to the STFT.

Parameters:

xTensor [shape=(…, L/2+1)]

The power spectrum.

Returns:

outTensor [shape=(…, C)]

The chroma filter bank output.

Examples

>>> sr = 16000
>>> x = diffsptk.sin(500, period=sr/440)
>>> stft = diffsptk.STFT(frame_length=512, frame_period=512, fft_length=512)
>>> chroma = diffsptk.ChromaFilterBankAnalysis(12, 512, sr)
>>> y = chroma(stft(x))
>>> y
tensor([[0.1146, 0.0574, 0.0457, 0.0468, 0.0519, 0.0789, 0.1736, 0.4285, 0.7416,
         1.0000, 0.7806, 0.3505]])

diffsptk.functional.chroma(x: Tensor, n_channel: int, sample_rate: int, norm: float = inf, use_power: bool = True) → Tensor

Apply chroma-filter banks to the STFT.

Parameters:

xTensor [shape=(…, L/2+1)]

The power spectrum.

n_channelint >= 1

The number of chroma filter banks, \(C\).

sample_rateint >= 1

The sample rate in Hz.

normfloat

The normalization factor.

use_powerbool

If True, use the power spectrum instead of the amplitude spectrum.

Returns:

outTensor [shape=(…, C)]

The chroma filter bank output.

See also

stft fbank