Module julius.core

Signal processing or PyTorch related utilities.

Functions

def hz_to_mel(freqs: torch.Tensor)

Converts a Tensor of frequencies in hertz to the mel scale. Uses the simple formula by O'Shaughnessy (1987).

Args

freqs : torch.Tensor

frequencies to convert.

def mel_frequencies(n_mels: int, fmin: float, fmax: float)

Return frequencies that are evenly spaced in mel scale.

Args

n_mels : int

number of frequencies to return.

fmin : float

start from this frequency (in Hz).

fmax : float

finish at this frequency (in Hz).

def mel_to_hz(mels: torch.Tensor)

Converts a Tensor of mel scaled frequencies to Hertz. Uses the simple formula by O'Shaughnessy (1987).

Args

mels : torch.Tensor

mel frequencies to convert.

def pad_to(tensor: torch.Tensor, target_length: int, mode: str = 'constant', value: float = 0)

Pad the given tensor to the given length, with 0s on the right.

def pure_tone(freq: float, sr: float = 128, dur: float = 4, device=None)

Return a pure tone, i.e. cosine.

Args

freq : float

frequency (in Hz)

sr : float

sample rate (in Hz)

dur : float

duration (in seconds)

def sinc(x: torch.Tensor)

Implementation of sinc, i.e. sin(x) / x

Warning: the input is not multiplied by pi!

def unfold(input, kernel_size: int, stride: int)

1D only unfolding similar to the one from PyTorch. However PyTorch unfold is extremely slow.

Given an input tensor of size [*, T] this will return a tensor [*, F, K] with K the kernel size, and F the number of frames. The i-th frame is a view onto i * stride: i * stride + kernel_size. This will automatically pad the input to cover at least once all entries in input.

Args

input : Tensor

tensor for which to return the frames.

kernel_size : int

size of each frame.

stride : int

stride between each frame.

Shape

• Inputs: input is [*, T]
• Output: [*, F, kernel_size] with F = 1 + ceil((T - kernel_size) / stride)

Warning: unlike PyTorch unfold, this will pad the input

so that any position in input is covered by at least one frame.

def volume(x: torch.Tensor, floor=1e-08)

Return the volume in dBFS.