Frequency Domain Linear Prediction for QMF Sub-bands and Applications to Audio Coding

This paper proposes an analysis technique for wide-band audio applications based on the predictability of the temporal evolution of Quadrature Mirror Filter (QMF) sub-band signals. The input audio signal is first decomposed into 64 sub-band signals using QMF decomposition. The temporal envelopes in critically sampled QMF sub-bands are approximated using frequency domain linear prediction applied over relatively long time segments (e.g. 1000 ms). Line Spectral Frequency parameters related to autoregressive models are computed and quantized in each frequency sub-band. The sub-band residuals are quantized in the frequency domain using a combination of split Vector Quantization (VQ) (for magnitudes) and uniform scalar quantization (for phases). In the decoder, the sub-band signal is reconstructed using the quantized residual and the corresponding quantized envelope. Finally, application of inverse QMF reconstructs the audio signal. Even with simple quantization techniques and without any sophisticated modules, the proposed audio coder provides encouraging results in objective quality tests. Also, the proposed coder is easily scalable across a wide range of bit-rates

Error Resilient Speech Coding Using Sub-band Hilbert Envelopes

Frequency Domain Linear Prediction (FDLP) represents a technique for auto-regressive modelling of Hilbert envelopes of a signal. In this paper, we propose a speech coding technique that uses FDLP in Quadrature Mirror Filter (QMF) sub-bands of short segments of the speech signal (25 ms). Line Spectral Frequency parameters related to au-toregressive models and the spectral components of the residual signals are transmitted. For simulating the effects of lossy transmission channels, bit-packets are dropped randomly. In the objective and subjective quality evaluations, the proposed FDLP speech codec is judged to be more resilient to bit-packet losses compared to the state-of-the-art Adaptive Multi-Rate Wide-Band (AMR-WB) codec at 12 kbps

Autoregressive Modelling of Hilbert Envelopes for Wide-band Audio Coding

Frequency Domain Linear Prediction (FDLP) represents the technique for approximating temporal envelopes of a signal using autoregressive models. In this paper, we propose a wide-band audio coding system exploiting FDLP. Specifically, FDLP is applied on critically sampled sub-bands to model the Hilbert envelopes. The residual of the linear prediction forms the Hilbert carrier, which is transmitted along with the envelope parameters. This process is reversed at the decoder to reconstruct the signal. In the objective and subjective quality evaluations, the FDLP based audio codec at $66$ kbps provides competitive results compared to the state-of-art codecs at similar bit-rates