# Multimode Tree-Coding of Speech with Pre-/Post-Weighting +
###### Abstract  
As speech-coding standards have improved over the years, so complexity has increased, and less emphasis been placed on low encoding/decoding delay. We present a low-complexity, low-delay speech codec based on tree-coding with sample-by-sample adaptive long- and short-code generators that incorporates pre- and post-filtering for perceptual weighting and multimode speech classification with comfort noise generation (CNG). The pre-/post-weighting filters adapt based on the code generator parameters available at both the encoder and decoder rather than the usual method that uses the input speech. The coding of the multiple speech modes and comfort noise generation is accomplished using the code generator adaptation algorithms, again, rather than using the input speech. Codec complexity comparisons are presented and operational rate distortion curves for several standardized speech codecs and the new codec are given. Finally, codec performance is shown in relation to theoretical rate distortion bounds. s +
Footnote †: This paper is an extended version of our paper published in [PERSON] and [PERSON], Multimode Tree Coding of Speech with Backward Pitch Prediction and Perceptual Pre- and Post-weighting, 46 th Annual Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 4-7 November 2012.  
used for the code searching in Code-Excited Linear Prediction (CELP). See Section 2 and references cited there. To reduce complexity, the perceptual weighting filter is moved out of the analysis-by-synthesis loop and incorporated as pre-weighting and post-weighting filters. Additionally, the short-term and long-term predictors as well as the codec gain are adapted on a sample-by-sample basis using what are called backward adaptive algorithms, which along with the shallow search depth, leads to lower delay than for codec such as AMR and EVS. Furthermore, the input speech is classified into modes, which are coded separately. Since this coder uses multiple modes, perceptual pre- and post-weighting, tree searching, and a pitch predictor, it is denoted as the Multimode Tree Coder with Pre- and Post-Weighting and Pitch prediction (MMT-WP) coder. The particular codec described and analyzed here, MMT-WP, was first presented in [3] where its performance was compared with a Multimode Tree Coder (MMT) based on G.727 and a squared error fidelity criterion and a MMT with pre-weighting and post-weighting to add perceptual shaping to the fidelity criterion, designated here as MMT-W, the multimode tree coder with pre- and post-weighting but no pitch prediction. It is shown in that paper that the MMT-WP outperforms the MMT codec without perceptual weighting and without pitch prediction in terms of PESQ-MOS [4]. These results are not included here, and substantial new discussion and performance results are presented as discussed at the end of this Introduction. The overall structure of the MMT-WP codec is presented in Section 3, which briefly introduces the several components. The G.727 waveform-following codec that uses backward adaptive short-term prediction and quantization is discussed in Section 4. The details of the predictor adaptation are included in Section 4.1 and the quantizer adaptation is covered in Section 4.2. These descriptions are included since parameters from G.727 are used in the voice activity detection and mode decisions and the reasons for zeros in the predictor are developed later as well. The G.727 performance is improved by the addition of a long-term pitch predictor, which is described in Section 5. The G.727 codec with the long-term pitch predictor forms the basis for what is called the Code Generator in Tree-Coding. Section 6 very briefly presents the basic building blocks of a tree coder, including the Code Generator, the Code Tree, the Tree Search, Algorithm, and the Perceptual Distortion Measure, which is usually inside the analysis-by-synthesis loop. The justification and analysis of moving the perceptual distortion measure outside the analysis-by-synthesis loop are given in Section 7.