nvidia.dali.fn.mfcc¶
- nvidia.dali.fn.mfcc(__input, /, *, axis=0, bytes_per_sample_hint=[0], dct_type=2, lifter=0.0, n_mfcc=20, normalize=False, preserve=False, seed=-1, device=None, name=None)¶
- Computes Mel Frequency Cepstral Coefficients (MFCC) from a mel spectrogram. - Supported backends
- ‘cpu’ 
- ‘gpu’ 
 
 - Parameters:
- __input (TensorList) – Input to the operator. 
- Keyword Arguments:
- axis (int, optional, default = 0) – - Axis over which the transform will be applied. - If a value is not provided, the outer-most dimension will be used. 
- bytes_per_sample_hint (int or list of int, optional, default = [0]) – - Output size hint, in bytes per sample. - If specified, the operator’s outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size. 
- dct_type (int, optional, default = 2) – - Discrete Cosine Transform type. - The supported types are 1, 2, 3, 4. The formulas that are used to calculate the DCT are equivalent to those described in https://en.wikipedia.org/wiki/Discrete_cosine_transform (the numbers correspond to types listed in https://en.wikipedia.org/wiki/Discrete_cosine_transform#Formal_definition). 
- lifter (float, optional, default = 0.0) – - Cepstral filtering coefficient, which is also known as the liftering coefficient. - If the lifter coefficient is greater than 0, the MFCCs will be scaled based on the following formula: - MFFC[i] = MFCC[i] * (1 + sin(pi * (i + 1) / lifter)) * (lifter / 2) 
- n_mfcc (int, optional, default = 20) – Number of MFCC coefficients. 
- normalize (bool, optional, default = False) – - If set to True, the DCT uses an ortho-normal basis. - Note - Normalization is not supported when dct_type=1. 
- preserve (bool, optional, default = False) – Prevents the operator from being removed from the graph even if its outputs are not used. 
- seed (int, optional, default = -1) – - Random seed. - If not provided, it will be populated based on the global seed of the pipeline. 
 
 
See also