Application of Prediction-based Lower Triangular Transform in Speech Coding

• Main Authors: Zong-Rong Wu, 吳宗融
• Other Authors: Yuan-Pei Lin
• Format: Others
• Language: en_US
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/35790423796777641343

碩士 === 國立交通大學 === 電機與控制工程系 === 88 === In this thesis, we proposed a transform coding method for speech coding,that is using a new nonunitary transform named Prediction-based Lower triangular Transform(PLT)\cite{PLT} to speech coding. It is like the Kahurene-Loeve Transform(KLT) that they has the same decorrelation property. But PLT''s implementational cost is less than one half of KLT. The PLT can be factorized into simple building blocks. We implement PLT by using the minimum noise structure that makes the coding gain of PLT is the same as KLT''s. The minimum noise structure has the following properties. (i)Its noise gain is unity. (ii)Structurally PR implementation. (iii)It can be apply for lossy or lossless compression. Performance of this transform coding method will be test by some speech data and compare with other compression ways.