angles ( None or Tensor) – Angles to use to initialize the algorithm.stft_enc ( Encoder ) – The Encoder(STFTFB()) object that was.Returned by Encoder(STFTFB), the magnitude spectrogram to be mag_specgram ( torch.Tensor) – (any, dim, ension, freq, frames) as.griffin_lim ( mag_specgram, stft_enc, angles=None, istft_dec=None, n_iter=6, momentum=0.9 ) ¶Įstimates matching phase from magnitude spectogram using the Np.array – the synthesis window to use for perfectly inverting the STFT. hop_size ( int) – Hop size in number of samples.analysis_window ( np.array) – Analysis window of the transform.perfect_synthesis_window ( analysis_window, hop_size ) ¶ Computes a window for perfect synthesis given an analysis window and a hop size. window ( numpy.ndarray, optional) – If None, defaults toĪbstract method for filters.stride ( int, optional) – Stride of the convolution (hop size).kernel_size ( int) – Length of the filters (i.e the window).STFTFB ( n_filters, kernel_size, stride=None, window=None, **kwargs ) ¶ Manuel Pariente, Samuele Cornell,Īntoine Deleforge, Emmanuel Vincent. : “Filterbank design for end-to-end speech separation”. : “Speaker Recognition from raw waveform with SincNet”. min_band_hz ( int, optional) – Lowest band frequency allowed (Hz).min_low_hz ( int, optional) – Lowest low frequency allowed (Hz).sample_rate ( int, optional) – The sample rate (used for initialization).stride ( int, optional) – Stride of the convolution.Parts) will have parameters, the other half will correspond to the Modified and extended from from Parameters: ParamSincFB ( n_filters, kernel_size, stride=None, sample_rate=16000, min_low_hz=50, min_band_hz=50 ) ¶īases: _dec.FilterbankĮxtension of the parameterized filterbank from proposed in. Identifier ( str or Callable or None) – the filterbank identifier. Is callable (already a Filterbank for example). Returns a filterbank class from a string. **kwargs – Arguments which will be passed to the filterbank classĪdditionally to the usual n_filters, kernel_size and stride.Ĭlass asteroid.filterbanks.output_padding ( int) – Additional size added to one side of the output shape.Which of Encoder or Decoder will be the pseudo inverse of who_is_pinv ( str, optional) – If None, no pseudo-inverse filters willīe used.To choose among [ 'free', 'analytic_free', fb_name ( str, className) – Filterbank family from which to make encoderĪnd decoder.make_enc_dec ¶Ĭreates congruent encoder and decoder from the same filterbank family. Returns an Decoder, pseudo inverse of a filterbank or Encoder. Torch.Tensor – The corresponding time domain signal.Ĭlassmethod pinv_of ( filterbank ) ¶ forward ( spec ) ¶Īpplies transposed convolution to a TF representation. Notes padding and output_padding arguments are directly passed toį.conv_transpose1d. output_padding ( int) – Additional size added to one side of the.filterbank ( Filterbank) – The filterbank to use as an decoder.Decoder ( filterbank, is_pinv=False, padding=0, output_padding=0 ) ¶Īdd decoding methods to Filterbank classes. > ( time, ) -> ( freq, conv_time ) > ( batch, time ) -> ( batch, freq, conv_time ) # Avoid > if as_conv1d : > ( batch, 1, time ) -> ( batch, freq, conv_time ) > ( batch, chan, time ) -> ( batch, chan, freq, conv_time ) > else : > ( batch, chan, time ) -> ( batch, chan, freq, conv_time ) > ( batch, any, dim, time ) -> ( batch, any, dim, freq, conv_time ) classmethod pinv_of ( filterbank, **kwargs ) ¶įilterbank or Decoder. :param waveform: any tensor with samples along the padding ( int) – Zero-padding added to both sides of the input.Ĭonvolve input waveform with the filters from a filterbank.If False, will output a tensor of shape (batch, 1, freq, conv_time). Will output a tensor of shape (batch, freq, conv_time). If True (default), forwarding input with shape (batch, 1, time) as_conv1d ( bool) – Whether to behave like nn.Conv1d.
is_pinv ( bool) – Whether to be the pseudo inverse of filterbank.filterbank ( Filterbank) – The filterbank to use.Encoder ( filterbank, is_pinv=False, as_conv1d=True, padding=0 ) ¶īases: _dec._EncDecĪdd encoding methods to Filterbank classes. Returns dictionary of arguments to re-instantiate the class. N_feats_out ( int) – Number of output filters. If None (default), set to kernel_size // 2. stride ( int, optional) – Stride of the conv or transposed conv.kernel_size ( int) – Length of the filters.Filterbank ( n_filters, kernel_size, stride=None ) ¶īases: ._MockObjectĮach subclass has to implement a filters property. Filterbank, Encoder and Decoder ¶ class asteroid.filterbanks.
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