Analysis-by-synthesis techniques are used in a wide variety of speech coding standards and applications for rates below 16 kbps. The presence of a long-term predictor, commonly known as the adaptive codebook, is critical to coder performance at the lower rates. Unfortunately, the encoding rate and computational requirements for high-quality encoding of pitch filter parameters can be excessive. Several popular approaches explore the trade-off between predictor order, allocated bit rate, and computational requirements for long-term predictor optimization. We investigate the relative performance of several long-term predictor structures and present a new approach to vector quantization of the pitch filter coefficients having a subjective quality equivalent to other schemes, but at a lower coding rate and requiring significantly less closed-loop computation. The performance is evaluated in a variable-rate CELP coder at an average rate of 2 kbps and in Federal Standard 1016 CELP.

Code-excited linear prediction (CELP) is the predominant methodology for communications quality speech coding below 8 kbps, and several variable-rate CELP schemes have been discussed in the literature, including QCELP, the variable-rate wideband digital cellular mobile radio speech coding standard specified in IS-95. A key component of these speech coders is the detection and classification of speech activity, and several cues for rate variation have been studied, such as measuring the short-term speech energy, deciding whether the speech is voiced or unvoiced, or making more sophisticated phonetic classifications. We present a new method for rate variation based on a measure of subband spectral flatness, called spectral entropy. Spectral entropy is a normalized indicator of the texture of the input spectrum and is thus less dependent on speech and background noise energy variations. We present some results on the use of spectral entropy for voice activity detection across subbands and then evaluate using spectral entropy for deriving mode and rate allocation cues for a variable-rate CELP coder operating at an average rate of 2 kbps. To achieve communications quality speech at this rate, we develop a new split-band vector quantization (VQ) technique for representing the line spectral pairs and a multiple codebook approach for efficiently quantizing the coefficients of a three-tap pitch predictor, called lag-indexed VQ.

The presence of a pitch predictor is critical to low-rate performance of CELP coders. Unfortunately the rate required for high-quality encoding of pitch filter parameters is often a large fraction of the available bandwidth. Moreover, the application of analysis-by-synthesis techniques to pitch filter optimization can require excessive computation. We present a vector quantization (VQ) approach for coding pitch filter parameters which maintains a subjective quality equivalent to other coding schemes while requiring lower (variable) rate with less closed-loop computation than other VQ techniques.

We introduce an approach to speech segment classification that differs from the usual energy, correlation, and zero-crossing criteria. Instead, we measure the gross shape of the short-term speech spectrum using spectral entropy to derive some indication of effective bandwidth. We propose to lower the required encoding rate by compensating for dynamic variations in signal bandwidth. We show that the spectral entropy can be used effectively to determine regions of voicing activity even in extreme background noise.>