Speech Communication

Contains table of contents for Part IV, table of contents for Section 1, an introduction, reports on seven research projects and a list of publications.C.J. Lebel FellowshipDennis Klatt Memorial FundNational Institutes of Health Grant T32-DC00005National Institutes of Health Grant R01-DC00075National Institutes of Health Grant F32-DC00015National Institutes of Health Grant R01-DC00266National Institutes of Health Grant P01-DC00361National Institutes of Health Grant R01-DC00776National Science Foundation Grant IRI 89-10561National Science Foundation Grant IRI 88-05680National Science Foundation Grant INT 90-2471

Spectrographic Analysis of Second Language Speech: Investigating the Effects of L1

Technological advances in Digital Signal Processing over the last decade have provided applied linguists with a number of computerized applications for speech analysis which can be of benefit to both the researcher and the instructor. This research project explores the techniques of speech spectrography and implements methods of acoustic phonetics to current issues in Second Language Acquisition theory. Specifically, the effects of vowel production in one\u27s native language on the targets in a second language are investigated. Acoustic measurements of English vowels spoken by Japanese students were compared with measurements of native Japanese vowels and American English vowels. In addition, these data were compared with measurements of learner speech from a variety of native language backgrounds. Vowels from both groups of non-native English speakers showed tendencies toward the center of the vowel space. The less-experienced group showed greater token-to-token variability across height parameters than across frontedness parameters while the more experienced group showed no difference for parameters. Both groups exhibited greater frontedness than height variability between speakers which can be explained in part by differences in vocal tract size. In addition, Flege\u27s Speech Learning Model was tested. Data did not support the hypothesis that similar vowels are more difficult to produce than different vowels. ANOVA tests showed that large LI vowel inventories do not advantage learners of languages with many vowels. The results suggest that the unique qualities of L2 speech may have more to do with developmental processes than L 1 interference

Fast Speech in Unit Selection Speech Synthesis

Moers-Prinz D. Fast Speech in Unit Selection Speech Synthesis. Bielefeld: Universität Bielefeld; 2020.Speech synthesis is part of the everyday life of many people with severe visual disabilities. For those who are reliant on assistive speech technology the possibility to choose a fast speaking rate is reported to be essential. But also expressive speech synthesis and other spoken language interfaces may require an integration of fast speech. Architectures like formant or diphone synthesis are able to produce synthetic speech at fast speech rates, but the generated speech does not sound very natural. Unit selection synthesis systems, however, are capable of delivering more natural output. Nevertheless, fast speech has not been adequately implemented into such systems to date. Thus, the goal of the work presented here was to determine an optimal strategy for modeling fast speech in unit selection speech synthesis to provide potential users with a more natural sounding alternative for fast speech output