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We propose the adaptive cascade recursive least squares with subsection adaptation (CRLS-SA) algorithm for direct estimation of line spectral frequencies (LSF) for use in speech coding. The least squares based CRLS-SA algorithm has a low computational complexity since each section is adapted independently from other sections. Using CRLS-SA, the LSF can be obtained directly from the coefficients of each section of the CRLS-SA structure. Two CRLS-SA approaches can be used for estimating LSF: use CRLS-SA as an AR inverse filter and obtain the LSF by converting the coefficients of each second order filter using a look-up table or, alternatively, construct a cascade of second order LSF polynomials P(z) and Q(z), and adapt each using CRLS-SA. The results show that the LSF estimates from CRLS-SA are competitive with the results obtained by the popular autocorrelation method followed by approximation using Chebyshev polynomials.

• Speech coding
• Direct line spectral frequency adaptation
• Second order cascade sections
• Adaptive cascade recursive least squares
• Subsection adaptation
• Low computational complexity
• Line spectral frequencies estimation
• Speech coding
• Least squares based CRLS-SA algorithm
• LSF
• Linear prediction coefficients
• AR inverse filter
• Second order filter
• Look-up table
• Second order LSF polynomials
• LSF estimates
• Autocorrelation method
• Chebyshev polynomials approximation
• CELP
• Least-squares based cascade adaptive filter