JOURNAL ARTICLE

Between Sound and Voice: Teaching Chinese Tones To Non-Tonal Language Speakers

Ewa Zajdler

Year: 2021 Journal:   Roczniki Humanistyczne Vol: 69 (9)Pages: 141-158   Publisher: The Learned Society of the John Paul II Catholic University of Lublin

Abstract

The production of highly intelligible syllables in Mandarin Chinese entails a successful production of tones, which poses a challenge for learners of Chinese as a foreign language. The aim of the current paper is to address this issue by identifying the key tonal features contributing to tone intelligibility in the lexemes produced by Polish learners of Mandarin Chinese as a foreign language. Samples of Polish female students’ tonal pronunciations at two stages of learning were selected and compared with productions made by a female native speaker of Mandarin Chinese from Taiwan. Four syllables produced by the students were selected from a corpus of read-out passages which had already been assessed for the intelligibility of monosyllabic lexemes by native judges. The students’ pronunciation samples (whose pronunciation improved from the A1 minus language level to A2) were analysed using pitch, fundamental frequency contour, and register span criteria, and then compared to the female native speaker’s pronunciations of the same syllables. Importantly, before the results of this analysis are presented, the simplified model of tones widely used in language instruction is compared and contrasted with the acoustic analysis of tonal productions made by the native speaker. This is done to show to what extent the simplified, widely used model reflects real-life tonal productions.

Keywords:
Mandarin Chinese Pronunciation Linguistics Intelligibility (philosophy) Tone (literature) Chinese as a foreign language First language Computer science Foreign language Second language Speech recognition Psychology

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Topics

Phonetics and Phonology Research
Social Sciences →  Psychology →  Experimental and Cognitive Psychology
Linguistic Studies and Language Acquisition
Physical Sciences →  Computer Science →  Artificial Intelligence

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