lpc#
- diffsptk.LPC#
alias of
LinearPredictiveCodingAnalysis
- class diffsptk.LinearPredictiveCodingAnalysis(frame_length, lpc_order, eps=1e-06)[source]#
See this page for details. Double precision is recommended.
- Parameters:
- frame_lengthint > M
Frame length, \(L\).
- lpc_orderint >= 0
Order of LPC, \(M\).
- epsfloat >= 0
A small value to improve numerical stability.
- forward(x)[source]#
Compute LPC coefficients.
- Parameters:
- xTensor [shape=(…, L)]
Framed waveform.
- Returns:
- outTensor [shape=(…, M+1)]
Gain and LPC coefficients.
Examples
>>> x = diffsptk.nrand(4) tensor([ 0.8226, -0.0284, -0.5715, 0.2127, 0.1217]) >>> lpc = diffsptk.LPC(5, 2) >>> a = lpc(x) >>> a tensor([0.8726, 0.1475, 0.5270])