Speech Compression With Masked Modulated Lapped Transform And SPIHT Algorithm

-A new method of speech compression using the Modulated Lapped Transform(MLT) and Set Partitioning In Hierarchical Trees (SPIHT) algorithm is proposed in this paper. The improvement in the signal with the application of masking with Psychoacoustic model has also been discussed. The proposed scheme is based on the combination of the Modulated Lapped Transform(MLT) and SPIHT. This paper also describes an excitation level based psychoacoustic model to estimate the simultaneous masking threshold for speech coding. The system has the following stages. 1) a windowing function; 2) a time-to-frequency transformation; 3) an excitation level calculation block 4) a correction factor for estimating masking threshold; 5) the inclusion of the absolute masking threshold; 6) the output Signal-to-Masking ratio. We evaluated the performance by integrating the psychoacoustic model into speech coding. Comparisons are also made with Plain LPC Coder, Voice Excited LPC Coder with the coding of the residual signal with DCT, Voice Excited LPC Coder with the coding of the residual signal with MLT, Voice Excited LPC Coder with the coding of the residual signal with MLT and SPIHT. The performance of the coders described has been assessed by computer simulation in terms of a) Signal –to –noise ratio (SNR) b) Compression ratio c) Percent Root mean square Difference(PRD). d) Informal subjective listening test.