Adaptive postfiltering has become a common part of speech coding standards based on the Linear Prediction Analysis-by-Synthesis algorithm to decrease audible coding noise. However, a conventional adaptive postfilter is based on empirical assumptions of masking phenomena, which sometimes makes it hard to balance between noise reduction and speech distortion. / This thesis introduces a novel perceptual postfiltering system for low bit rate speech coders. The proposed postfilter works at the decoder, as is the case for the conventional adaptive postfilter. Specific human auditory properties are considered in the postfilter design to improve speech quality. A Gaussian Mixture Model based Minimum Mean Squared Error estimation of the perceptual postfilter is performed with the received information at the decoder. Perceptual postfiltering is then applied to the reconstructed speech to improve speech quality. Test results show that the proposed system gives better perceptual speech quality over conventional adaptive postfiltering.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.112563 |
| Date | January 2007 |
| Creators | Chen, Wei, 1976- |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Engineering (Department of Electrical and Computer Engineering.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002713681, proquestno: AAIMR51453, Theses scanned by UMI/ProQuest. |
Page generated in 0.0111 seconds