Speech enhancement and coding at medium-low rates

Abstract

In this dissertation work, speech enhancement and coding at medium-low rates (i.e., 4.8 to 16 kbits/s) have been studied. This dissertation work may be divided into five parts. First, adaptive linear prediction based on the frequency-domain block least-mean-square (FBLMS) adaptation algorithm has been studied. A new frequency-weighted block least-mean-square (FWBLMS) algorithm that minimizes frequency-weighted block mean-squared error is proposed and applied to linear prediction of speech. Also, the optimum convergence factors of various adaptive digital filter (ADF) algorithms are derived analytically. In adaptive linear prediction of speech, the use of the FWBLMS algorithm gives several advantages. These include direct residual extraction, the existence of time- and frequency-domain information of input and residual signals and prediction coefficients, inherent noise spectral shaping effect and simultaneous enhancement and coding by the spectral subtraction method in the frequency domain without block delay. Application of the FWBLMS algorithm to multi-rate vocoding is also discussed in detail. Second, enhancement of noisy speech corrupted by white or colored noise is studied. The unconstrained FBLMS (UFBLMS) algorithm with fast convergence speed for correlated input is newly applied to speech processing. For enhancement of speech degraded by white noise, the spectral subtraction method, Wiener filtering and the UFBLMS algorithm are investigated, and their performances are compared by various objective measures. The UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmental frequency-weighted signal-to-quantization noise ($\mbox{FWSQNR}_\mbox{SEG}$) when SNR of speech is in the range of 0 to 10 dB. Furthermore, when the UFBLMS algorithm is used, high-pass filtering may be combined with the enhancement algorithm to improve speech quality and intelligibility. For enhancement of noisy speech corru...