title: Objective speech quality assessment and the RPE-LTP coding algorithm in different noise and language conditions.
abstract: The formulation of reliable signal processing algorithms for speech coding and synthesis require the selection of a prior criterion of performance. Though coding efficiency (bits/second) or computational requirements can be used, a final performance measure must always include speech quality. In this paper, three objective speech quality measures are considered with respect to quality assessment for American English, noisy American English, and noise-free versions of seven languages. The purpose is to determine whether objective quality measures can be used to quantify changes in quality for a given voice coding method, with a known subjective performance level, as background noise or language conditions are changed. The speech coding algorithm chosen is regular-pulse excitation with long-term prediction (RPE-LTP), which has been chosen as the standard voice compression algorithm for the European Digital Mobile Radio system. Three areas are considered for objective quality assessment which include: (i) vocoder performance for American English in a noise-free environment, (ii) speech quality variation for three additive background noise sources, and (iii) noise-free performance for seven languages which include English, Japanese, Finnish, German, Hindi, Spanish, and French. It is suggested that although existing objective quality measures will never replace subjective testing, they can be a useful means of assessing changes in performance, identifying areas for improvement in algorithm design, and augmenting subjective quality tests for voice coding/compression algorithms in noise-free, noisy, and/or non-English applications.
authors.affiliation: Department of Electrical Engineering, Duke University, Durham, North Carolina 27708-0291.
authors.forename: J H
authors.initials: JH
authors.lastname: Hansen
authors.forename: S
authors.initials: S
authors.lastname: Nandkumar
mesh_terms: D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D007802:Language; D008297:Male; D008875:Middle Aged; D009622:Noise; D010700:Phonetics; D013018:Sound Spectrography; D013067:Speech Perception; D014833:Voice Quality