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    LpcResult

    source
    pub(all) struct LpcResult {
      coeffs : Array[Double]
      reflection : Array[Double]
      prediction_error : Double
    } derive(
    Debug    )

    Result of Levinson-Durbin LPC solver.

    LpcResult::to_repr

    source

    autocorrelation

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    fn autocorrelation(samples : Array[Double], max_lag : Int) -> Array[Double]

    Compute biased autocorrelation sequence up to max_lag.

    levinson_durbin

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    fn levinson_durbin(r : Array[Double], order : Int) -> Result[LpcResult, 
    MelError    ]

    Solve LPC all-pole filter via Levinson-Durbin recursion algorithm.

    lpc

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    fn lpc(samples : Array[Double], order : Int) -> Result[LpcResult, 
    MelError    ]

    Direct LPC analysis on a frame of audio samples.

    lpc_features

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    fn lpc_features(samples : Array[Double], order : Int, frame_length : Int, hop_length : Int) -> Result[
    FeatureMatrix    , 
    MelError    ]

    Extract frame-wise LPC feature matrix [order x n_frames].

    lpc_residual

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    fn lpc_residual(samples : Array[Double], lpc_coeffs : Array[Double]) -> Array[Double]

    Compute linear prediction residual (inverse filtering): e[n] = x[n] - sum_{k=1}^p a_k * x[n-k].

    lpc_to_lpcc

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    fn lpc_to_lpcc(lpc_coeffs : Array[Double], prediction_error : Double, n_lpcc : Int) -> Array[Double]

    Convert LPC filter coefficients to Linear Prediction Cepstral Coefficients (LPCC).

    lpcc_features

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    fn lpcc_features(samples : Array[Double], order : Int, n_lpcc : Int, frame_length : Int, hop_length : Int) -> Result[
    FeatureMatrix    , 
    MelError    ]

    Extract frame-wise Linear Prediction Cepstral Coefficients (LPCC) matrix [n_lpcc x n_frames].

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