Entropy Coding of Quantized Spectral Components in Fdlp Audio Codec

Audio codec based on Frequency Domain Linear Prediction (FDLP) exploits auto-regressive modeling to approximate instantaneous energy in critical frequency sub-bands of relatively long input segments. Current version of the FDLP codec operating at 66 kbps has shown to provide comparable subjective listening quality results to the state-of-the-art codecs on similar bit-rates even without employing strategic blocks, such as entropy coding or simultaneous masking. This paper describes an experimental work to increase compression efficiency of the FDLP codec provided by employing entropy coding. Unlike traditionally used Huffman coding in current audio coding systems, we describe an efficient way to exploit Arithmetic coding to entropy compress quantized magnitude spectral components of the sub-band FDLP residuals. Such approach outperforms Huffman coding algorithm and provides more than 3 kbps bit-rate reduction.