acorr

Functions

int main(int argc, char *argv[])

acorr [ option ] [ infile ]

• -l int

  • frame length \((1 \le L)\)

• -m int

  • order of autocorrelation coefficients \((0 \le M)\)

• -q int

  • input format

    • 0 amplitude spectrum in dB

    • 1 log amplitude spectrum

    • 2 amplitude spectrum

    • 3 power spectrum

    • 4 windowed waveform

• -o int

  • output format

    • 0 autocorrelation

    • 1 normalized autocorrelation

    • 2 biased autocorrelation

    • 3 unbiased autocorrelation

• infile str

  • double-type data sequence

• stdout

  • double-type autocorrelation sequence.

If -o 1, output the normalized autocorrelation:

\[ \begin{array}{cccc} 1, & r(1)/r(0), & \ldots, & r(M)/r(0), \end{array} \]

where \(r(m)\) is the \(m\)-th autocorrelation coefficient. If -o 2, output the biased autocorrelation function:

\[ \begin{array}{cccc} r(0)/L, & r(1)/L, & \ldots, & r(M)/L. \end{array} \]

If -o 3, output the unbiased autocorrelation function:

\[ \begin{array}{cccc} r(0)/L, & r(1)/(L-1), & \ldots, & r(M)/(L-M). \end{array} \]

The below example extracts 10-th order autocorrelation coefficients from windowed waveform.

x2x +sd data.short | frame | window | acorr -m 10 > data.acr

Parameters

• argc – [in] Number of arguments.

• argv – [in] Argument vector.

Returns

0 on success, 1 on failure.

See also

c2acr levdur lpc

class AutocorrelationAnalysis

Calculate autocorrelation from waveform or spectrum.

Public Functions

AutocorrelationAnalysis(int frame_length, int num_order, bool waveform_input)

Parameters

• frame_length – [in] Frame length or number of FFT bins, \(L\).

• num_order – [in] Order of autocorrelation, \(M\).

• waveform_input – [in] If true, assume waveform input.

inline bool IsValid() const

Returns

True if this object is valid.

bool Run(const std::vector<double> &input, std::vector<double> *autocorrelation, AutocorrelationAnalysis::Buffer *buffer) const

Parameters

• input – [in] \(L\)-length waveform or \((L/2+1)\)-length power spectrum.

• autocorrelation – [out] \(M\)-th order autocorrelation coefficients.

• buffer – [out] Buffer.

Returns

True on success, false on failure.

class Buffer

Buffer for AutocorrelationAnalysis class.

class WaveformToAutocorrelation

Calculate autocorrelation.

The input is the framed waveform signal:

\[ \begin{array}{cccc} x(0), & x(1), & \ldots, & x(L-1), \end{array} \]

where \(L\) is the frame length. The output is the \(M\)-th order autocorrelation coefficients:

\[ \begin{array}{cccc} r(0), & r(1), & \ldots, & r(M). \end{array} \]

The autocorrelation is given by

\[ r(m) = \sum_{l=0}^{L-1-m} x(l)x(l+m), \]

where \(m\) is the lag.

Public Functions

WaveformToAutocorrelation(int frame_length, int num_order)

Parameters

• frame_length – [in] Frame length, \(L\).

• num_order – [in] Order of autocorrelation, \(M\).

inline int GetFrameLength() const

Returns

Frame length.

inline int GetNumOrder() const

Returns

Order of autocorrelation.

inline bool IsValid() const

Returns

True if this object is valid.

bool Run(const std::vector<double> &waveform, std::vector<double> *autocorrelation) const

Parameters

• waveform – [in] \(L\)-length framed waveform.

• autocorrelation – [out] \(M\)-th order autocorrelation coefficients.

class SpectrumToAutocorrelation

Calculate autocorrelation from power spectrum.

The input is the half of power spectrum:

\[ \begin{array}{cccc} |X(0)|^2, & |X(1)|^2, & \ldots, & |X(L/2)|^2, \end{array} \]

where \(L\) is the FFT length. The output is the \(M\)-th order autocorrelation coefficients:

\[ \begin{array}{cccc} r(0), & r(1), & \ldots, & r(M). \end{array} \]

The autocorrelation is given by

\[ r(m) = \frac{1}{L} \sum_{l=0}^{L-1} |X(l)|^2 e^{j \frac{2\pi}{L} lm}, \]

where \(m\) is the lag.

Public Functions

SpectrumToAutocorrelation(int fft_length, int num_order)

Parameters

• fft_length – [in] Number of FFT bins, \(N\).

• num_order – [in] Order of autocorrelation, \(M\).

inline int GetFftLength() const

Returns

FFT length.

inline int GetNumOrder() const

Returns

Order of autocorrelation.

inline bool IsValid() const

Returns

True if this object is valid.

bool Run(const std::vector<double> &power_spectrum, std::vector<double> *autocorrelation, SpectrumToAutocorrelation::Buffer *buffer) const

Parameters

• power_spectrum – [in] \((L/2+1)\)-length power spectrum.

• autocorrelation – [out] \(M\)-th order autocorrelation coefficients.

• buffer – [out] Buffer.

Returns

True on success, false on failure.

class Buffer

Buffer for SpectrumToAutocorrelation class.