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Katya Petrova; Kyle Jasmin; Kazuya Saito; Adam T. Tierney – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Languages differ in the importance of acoustic dimensions for speech categorization. This poses a potential challenge for second language (L2) learners, and the extent to which adult L2 learners can acquire new perceptual strategies for speech categorization remains unclear. This study investigated the effects of extensive English L2 immersion on…
Descriptors: Second Language Learning, Second Language Instruction, Suprasegmentals, Mandarin Chinese
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Teeranon, Phanintra – Journal of Language and Linguistic Studies, 2020
This study investigates the acoustic characteristics of Thai tones produced by Chinese students learning Thai through the "Tone Application", and conducts an attitude test towards the use of the Tone Application. A comparison of Thai tones pronounced by the participants with 40 native Thai speakers was also conducted. The acoustic…
Descriptors: Tone Languages, Intonation, Thai, Chinese
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Walker, Peter – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Lexical sound symbolism in language appears to exploit the feature associations embedded in cross-sensory correspondences. For example, words incorporating relatively high acoustic frequencies (i.e., front/close rather than back/open vowels) are deemed more appropriate as names for concepts associated with brightness, lightness in weight,…
Descriptors: Sensory Integration, Intonation, Suprasegmentals, Phonology
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Bird, Steven; Lee, Haejoong – Language Documentation & Conservation, 2014
Investigating a tone language involves careful transcription of tone on words and phrases. This is challenging when the phonological categories--the tones or melodies--have not been identified. Effects such as coarticulation, sandhi, and phrase-level prosody appear as obstacles to early elicitation and classification of tone. This article presents…
Descriptors: Classification, Computational Linguistics, Tone Languages, Intonation
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Bahreini, Kiavash; Nadolski, Rob; Westera, Wim – Education and Information Technologies, 2016
This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…
Descriptors: Affective Behavior, Emotional Response, Electronic Learning, Recognition (Psychology)