par2lpc
Functions
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int main(int argc, char *argv[])
par2lpc [ option ] [ infile ]
-m int
order of coefficients \((0 \le M)\)
infile str
double-type PARCOR coefficients
stdout
double-type LPC coefficients
The below example converts PARCOR coefficients into LPC coefficients:
par2lpc < data.rc > data.lpc
The converted LPC coefficients can be reverted by
lpc2par < data.lpc > data.rc
- Parameters:
argc – [in] Number of arguments.
argv – [in] Argument vector.
- Returns:
0 on success, 1 on failure.
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class ParcorCoefficientsToLinearPredictiveCoefficients
Convert PARCOR coefficients to LPC coefficients.
The input is the \(M\)-th order PARCOR coefficients:
\[ \begin{array}{cccc} K, & k(1), & \ldots, & k(M), \end{array} \]and the output is the \(M\)-th order LPC coefficients:\[ \begin{array}{cccc} K, & a(1), & \ldots, & a(M), \end{array} \]where \(K\) is the gain. The conversion is given by the following recursion formula:\[\begin{split} a^{(i)}(m) = a^{(i-1)}(m) + k(i) a^{(i-1)}(i-m) \\ i = 2,\ldots,M \end{split}\]with the initial condition \(a^{(i)}(i)=k(i)\) for \(i = 1,\ldots,M-1\). The outputs can then be written as\[\begin{split} a(m) = \left\{ \begin{array}{ll} a^{(M)}(m), & 1 \le m < M \\ k(m). & m = M \end{array} \right. \end{split}\]Public Functions
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explicit ParcorCoefficientsToLinearPredictiveCoefficients(int num_order)
- Parameters:
num_order – [in] Order of coefficients.
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inline int GetNumOrder() const
- Returns:
Order of coefficients.
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inline bool IsValid() const
- Returns:
True if this object is valid.
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bool Run(const std::vector<double> &parcor_coefficients, std::vector<double> *linear_predictive_coefficients, ParcorCoefficientsToLinearPredictiveCoefficients::Buffer *buffer) const
- Parameters:
parcor_coefficients – [in] \(M\)-th order PARCOR coefficients.
linear_predictive_coefficients – [out] \(M\)-th order LPC coefficients.
buffer – [out] Buffer.
- Returns:
True on success, false on failure.
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bool Run(std::vector<double> *input_and_output, ParcorCoefficientsToLinearPredictiveCoefficients::Buffer *buffer) const
- Parameters:
input_and_output – [inout] \(M\)-th order coefficients.
buffer – [out] Buffer.
- Returns:
True on success, false on failure.
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class Buffer
Buffer for ParcorCoefficientsToLinearPredictiveCoefficients class.
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explicit ParcorCoefficientsToLinearPredictiveCoefficients(int num_order)