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.