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Line Spectrum Pair Parameters (LSF) are important parameters in low rate speech coding. Implementing LSF transparent quantization with as few bits as possible is a research hotspot in the field of low-rate speech coding. Based on the theory of compressed sensing, this paper proposes a new adaptive reconstruction algorithm. At the encoding end, the algorithm performs frame type discrimination on the LSF of single frame or superframe after voice activation detection and then applies the compressed sensing method to observe and quantize the LSF parameters of the single frame or superframe. At the decoding end, parameters are adaptively selected according to every single frame or superframe type, so that the number of bits required to reconstruct the LSF is reduced. The experimental results show that the proposed algorithm can reduce the number of bits required for LSF reconstruction and improve the reconstruction quality under the appropriate codebook storage and search complexity.

Fast Adaptive Reconstruction Algorithm for Line Spectrum Pair Parameters Based on Compressed Sensing