Signal processing based segmentation and HMM based acoustic clustering of syllable segments for low bit rate segment vocoder at 1.4 Kbps

In this paper, we propose a novel approach for developing a segment-based vocoder at very low bit-rates. The segmental unit chosen for coding is a syllable. A signal processing technique called automatic group delay based segmentation is used to obtain syllable like segments. The segment codebook is prepared by acoustically clustering the syllable segments using a Hidden Markov Model (HMM) based unsupervised and incremental training algorithm. When the residual is modeled using MELP, a bit-rate of 1.4 Kbps is achieved. The synthesized speech quality is compared with that of the standard MELP codec at 2.4 Kbps using the objective evaluation measure, PESQ. copyright by EURASIP.