✦ LIBER ✦

Design and performance of tree-structured vector quantizers

✍ Scribed by Jianhua Lin; James A. Storer

Book ID: 113330560
Publisher: Elsevier Science
Year: 1994
Tongue: English
Weight: 908 KB
Volume: 30
Category: Article
ISSN: 0306-4573
DOI: 10.1016/0306-4573(94)90012-4

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Some issues related to fixed-rate pruned

✍ Moayeri, N. 📂 Article 📅 1995 🏛 IEEE 🌐 English ⚖ 863 KB

Design and performance of trellis vector

Design and performance of trellis vector quantizers for speech signals

✍ Juang, B.-H. 📂 Article 📅 1988 🏛 IEEE ⚖ 893 KB

Tree-structured product-codebook vector

Tree-structured product-codebook vector quantization

✍ Giovanni Poggi; Arturo R.P. Ragozini 📂 Article 📅 2001 🏛 Elsevier Science 🌐 English ⚖ 554 KB

To carry out vector quantization (VQ) on large vectors, and hence obtain a good performance, it is necessary to introduce some structural constraint in the encoder. Product-codebook VQ reduces memory storage and encoding complexity. Tree-structured VQ reduces encoding complexity as well, and allows

Design, performance, and complexity anal

Design, performance, and complexity analysis of residual trellis-coded vector quantizers

✍ Aksu, A.; Salehi, M. 📂 Article 📅 1998 🏛 IEEE 🌐 English ⚖ 155 KB

Optimal pruning for tree-structured vect

Optimal pruning for tree-structured vector quantization

✍ Jianhua Lin; James A. Storer; Martin Cohn 📂 Article 📅 1992 🏛 Elsevier Science 🌐 English ⚖ 718 KB

Tree-structured vector quantization for

Tree-structured vector quantization for speech recognition

✍ M. Barszcz; W. Chen; G. Boulianne; P. Kenny 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 90 KB

We describe some new methods for constructing discrete acoustic phonetic hidden Markov models (HMMs) using tree quantizers having very large numbers (16-64 K) of leaf nodes and tree-structured smoothing techniques. We consider two criteria for constructing tree quantizers (minimum distortion and min