Classification-Based Techniques for Digital Coding of Speech-plus-Noise

With the increasing demand for wireless voice services and limited bandwidth resources, it is critical to develop and implement coding techniques which use spectrum efficiently. One approach to increasing system capacity is to lower the bit rate of telephone speech. A typical telephone conversation contains approximately 40% speech and 60% silence or background acoustic noise. A reduction of the average coding rate can be achieved by using a Voice Activity Detection (VAD) unit to distinguish speech from silence or background noise. The VAD decision can be used to select different coding modes for speech and noise or to discontinue transmission during speech pauses. The quality of a telephone conversation using a VAD-based coding system depends on three major modules: the speech coder, the noise coder, and the VAD. Existing schemes for reduced-rate coding of background noise produce a signal that sounds different from the noise at the transmitting side. The frequent changes of the noise character between that produced during talk spurts (noise coded along with the speech) and that produced during speech pauses (noise coded at a reduced rate) are noticeable and can be annoying to the user. The objective of this thesis is to develop techniques that enhance the output quality of variable-rate and discontinuous-transmission speech coding systems operating in noisy acoustic environments during the pauses between speech bursts. We propose novel excitation models for natural-quality reduced-rate coding of background acoustic noise in voice communication systems. A better representation of the excitation signal in a noise-synthesis model is achieved by classifying the type of acoustic environment noise. Class-dependent residual substitution is used at the receive side to synthesize a background noise that sounds similar to the background noise at the transmit side. The improvement in the quality of synthesized noise during speech gaps helps in preserving noise continuity between talk spurts and speech pauses, and enhances the overall perceived quality of a conversation.