Perceptual Coding of Narrowband Audio Signals

New applications such as Internet broadcast and communications, consumer multimedia products, digital AM broadcast and satellite networks are emerging. Those applications require moderate audio quality without annoying artifacts at bit rates below 16 kbit/s. Although speech coders provide high speech quality at bit rates around 8 kbit/s, they perform poorly when encoding audio signals. In this thesis, we present a novel transform coding paradigm based on the characteristics of the human hearing system. The proposed encoder, i.e., Narrowband Perceptual Audio Coder (NPAC), can accommodate a wide range of narrowband audio inputs without annoying artifacts at bit rates down to 8 kbit/s. NPAC employs a variety of algorithms to remove the perceptually irrelevant parts and statistical redundancies of the input signal. The new algorithms used in NPAC include a perceptual error measure in training the codebooks and selecting the best codewords, perceptually-based bit allocation algorithms and an adaptive predictive scheme to vector quantize the scale factors. The proposed encoder has moderate complexity and delivers good quality for narrowband audio inputs at around 1 bit/sample. Informal subjective tests have been conducted to compare the performance of NPAC with an 8 kbit/s commercially-available audio coder. The tests results show that NPAC performs better for both music and speech inputs.