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John S. Logan

Researcher at Carleton University

Publications -  17
Citations -  1986

John S. Logan is an academic researcher from Carleton University. The author has contributed to research in topics: Intelligibility (communication) & Verbal learning. The author has an hindex of 9, co-authored 17 publications receiving 1883 citations. Previous affiliations of John S. Logan include Indiana University.

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Training Japanese listeners to identify English /r/ and /l/: A first report

TL;DR: The results demonstrate the importance of stimulus variability and task-related factors in training nonnative speakers to perceive novel phonetic contrasts that are not distinctive in their native language.
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Training Japanese listeners to identify English /r/ and /l/. II: The role of phonetic environment and talker variability in learning new perceptual categories

TL;DR: The results of the present experiments suggest that variability plays an important role in perceptual learning and robust category formation and that listeners develop talker-specific, context-dependent representations for new phonetic categories by selectively shifting attention toward the contrastive dimensions of the non-native phonetic category categories.
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On the nature of talker variability effects on recall of spoken word lists.

TL;DR: In a recent study, Martin, Pisoni, and Martin this article examined the effect of talker variability on the recall of spoken words in rehearsal and perceptual encoding, and found that recall of multiple-talker lists was affected much more than single-talkers lists by changes in presentation rate.
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Segmental intelligibility of synthetic speech produced by rule.

TL;DR: An investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener.
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Perception of synthetic speech produced automatically by rule: Intelligibility of eight text-to-speech systems

TL;DR: The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants, and suggestions for future research on improving the quality of synthetic speech are considered.