Spectral noise shaping: improvements in speech/audio codec based on linear prediction in spectral domain

Audio coding based on Frequency Domain Linear Prediction (FDLP) uses autoregressive models to approximate Hilbert envelopes in frequency sub-bands. Although the basic technique achieves good coding efficiency, there is a need to improve the reconstructed signal quality for tonal signals with impulsive spectral content. For such signals, the quantization noise in the FDLP codec appears as frequency components not present in the input signal. In this paper, we propose a technique of Spectral Noise Shaping (SNS) for improving the quality of tonal signals by applying a Time Domain Linear Prediction (TDLP) filter prior to the FDLP processing. The inverse TDLP filter at the decoder shapes the quantization noise to reduce the artifacts. Application of the SNS technique to the FDLP codec improves the quality of the tonal signals without affecting the bit-rate. Performance evaluation is done with Perceptual Evaluation of Audio Quality (PEAQ) scores and with subjective listening tests.