Abstract. A handset compensation technique for speaker verification from coded telephone speech is proposed. The proposed technique combines handset selectors with stochastic feature transformation to reduce the acoustic mismatch between different handsets and different speech coders. Coder-dependent GMM-based handset selectors are trained to identify the most likely handset used by the claimants. Stochastic feature transformations are then applied to remove the acoustic distortion introduced by the coder and the handset. Experimental results show that the proposed technique outperforms the CMS approach and significantly reduces the error rates under six different coders with bit rates ranging from 2.4 kb/s to 64 kb/s. Strong correlation between speech quality and verification performance is also observed.
A variable bit rate multiband excited linear predictive speech coder is proposed in this paper. Speech signal is compressed in different bit rates ranging from 0.88 kbps to 2.6 kbps according to the mode of operation and the optimum V N V transition frequency. An average bit rate of 1.24 kbps is achieved. The proposed speech coder improves the speech quality by splitting the non-stationary speech segments for analysis. The V/UV distribution of a short-time speech spectrum is represented efficiently by using a closed-loop minimised VAJV transition frequency. Depending on the V N V transition frequency, the spectrum envelope is quantized in variable bit rate through embedded differential predictive scalar and vector quantizations of the LSP parameters. The proposed spectral quantization scheme results in a spectral distortion comparable to a fixed 24-bit 2-dimensional differential scalar quantization scheme.
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