International Conference on Chinese Language Learning and Teaching in the Digital Age Young Scholar Award Competition, Hong Kong, 25-27 November, 2011 Towards a Model of Second Language Word Production and Recognition in Mandarin Patrick Chun Kau Chu PhD Candidate School of Psychology University of New South Wales, Sydney, Australia Email correspondence: [email protected] Website: http://www.patrickchu.net/ 1 Aim of the study • Understand how Cantonese speakers’ production and recognition of second language (L2) Mandarin words is influenced by the first language (L1) lexical system 2 Pronunciation relationships between Cantonese and Mandarin words • There are many homophones (同音字) in Cantonese and Mandarin Character / meaning 聲 ‘sound’ Cantonese pronunciation 星 ‘star’ 尾 ‘tail’ /sing/ Mandarin pronunciation /sheng/ 美 ‘beauty’ /mei/ /xing/ /wei/ /mei/ ‘sound’ 聲音 /shengyin/ /xingyin/ ‘tail’ 尾巴 /weiba/ /meiba/ ‘tail’ =尾 Concept L1 Cantonese phonological representation Concept route ‘beauty’ =美 mei Concept route Lexical route L2 Mandarin phonological representation Mispronunciation occurrence wei mei 0% 25% mi 3 Pronunciation relationships between Cantonese and Mandarin (Zhang & Gao, 2000) Cantonese onset (聲母) /m/ Mandarin onset m w b Number of words 160 33 2 Percentage 82% 17% 1% Example 媽 ‘mother’ 萬 ‘ten thousand’ 剝 ‘to shell’ Cantonese pronunciation maa1 maan6 mok1 Mandarin pronunciation ma1 wan4 bo1, bao1 Cantonese rime (韻母) /ei/ Mandarin rime i ei in ü er Number of words 99 26 1 1 1 Percentage 77% 20% 1% 1% 1% Example 皮 ‘skin’ 悲 ‘sad’ 您 ‘you’ 履 ‘shoes’ 餌 ‘bait’ Cantonese pronunciation pei4 bei1 neii5 lei5 lei6 Mandarin pronunciation pi2 bei1 nin2 lü3 er3 4 L2 Mandarin word production model ‘tail’ =尾 Concept ‘beauty’ =美 L1 Cantonese phonological representation L1 Cantonese sublexical representation mei Sublexical route Concept route L2 Mandarin sublexical representation L2 Mandarin phonological output buffer wei Sublexical correspondence 3% Mispronunciation occurrence 0% Lexical route m ei 82% 17% 77% m w i 17% Lexical route Concept route ei mi wi 63% 13% mei 14% 25% Correlation between sublexical correspondence and mispronunciation occurrence = 0.35, p = .005 5 (Chu & Taft, LSHK ARF 2010) Major tone relationships between Cantonese and Mandarin (Zhang & Gao, 2000) Cantonese tone 1 2 3 4 5 6 Mandarin tone 1 3 4 2 3 4 Percentage 93% 89% 91% 93% 76% 94% Example 郊 ‘suburb’ 找 ‘find’ 怪 ‘strange’ 牛 ‘cow’ 偉 ‘great’ 又 ‘again’ Regular-tone Cantonese / Mandarin pronunciation gaau1 / jiao1 zaau2 / zhao3 gwai3 / gwai4 ngau4 / niu2 wai5 / wei3 jau6 / you4 Exception 魔 ‘devil’ 帽 ‘hat’ 傘‘umbrella’ 微 ‘little’ 市 ‘city’ 捕 ‘catch’ Cantonese / Mandarin pronunciation mo1 / mo2 mou2 / mao4 saan3 / san3 mei4 / wei1 si5 / shi4 bou6 / bu3 Irregular-tone 6 L2 Mandarin word production model: Incorporating the tone component Regular-tone word: 找 ‘find’ Cantonese: zaau2 Mandarin: zhao3 ‘find’ =找 Concept L1 Cantonese phonological representation ‘hat’ =帽 zaau2 Concept route mou2 Sublexical route Lexical route L1 Cantonese sublexical representation Concept route z 53% L2 Mandarin sublexical representation L2 Mandarin phonological output buffer Irregular-tone word: 帽 ‘hat’ Cantonese: mou2 Mandarin: mao4 zh 21% aau Sublexical route Lexical route m 2 ou 2 18% 61% 30% 89% 5% 82% 17% 49% 47% 89% 5% j ao iao 3 4 m w ao u 3 4 z zhao3 zao3 jiao3 29% 11% 5% zhao4 2% zao4 jiao4 mao4 mao3 mu3 wu3 mu4 wu4 0.6% 0.3% 2% 36% 34% 7% 2% 0.4% 7 Chinese character – Mandarin sound matching task (Chu & Taft, ICPhs 2011) • Materials Word Type Matched Mismatched zhao3 zhao4 > < mao4 mao3 Regular-tone words (e.g. 找 ‘find’ Cantonese: zaau2) Irregular-tone words (e.g. 帽 ‘hat’ Cantonese: mou2) • Dependent variables - Percentage of ‘yes’ responses 8 Further evidence for the use of the sublexical route in L2 Mandarin word production • Mandarin pinyin transcription task (Chu & Taft, EPC 2011) Sublexical unit Cantonese pronunciation Onset Regular word Irregular word Mandarin pronunciation (% correspondence) Example Mandarin pronunciation (% correspondence) d d (96%) 對 ‘correct’ t (2%) 突 ‘sudden’ Rime aai ai (59%) 帶 ‘bring’ a (2%) 拉 ‘pull’ Tone Tone 4 Tone 2 (93%) 農 ‘farm’ Tone 4 (4%) Mean error rate Example 期 ‘period’ Error analysis of irregular words 9 L2 Mandarin word recognition model Mispronunciation 魔 ‘devil’ mo2 mo1 Correct pronunciation 魔 ‘devil’ mo2 L2 Mandarin phonological input mo1 mo2 L2 Mandarin sublexical representation m Concept L1 Cantonese route Lexical route 98% m sublexical representation L1 Cantonese phonological representation Concept Sublexical route Sublexical route mo1 mo4 23% ‘devil’ =魔 ‘grind’ =磨 o 31% 27% o ok mok6 12% 17% ut ak 76% 4 mut6 3% ‘don’t’ =莫 m 2 13% Lexical route 98% m 6 mo2 mak6 2% ‘sink’ =沒 Concept route ‘wheat’ =麥 ‘touch’ =摸 1 31% 27% o ok 12% 17% ut mo1 25% 2% o ‘devil’ =魔 ak 83% 9% 1 3 mok1 mut3 22% ‘peel’ =剝 1% ‘plaster’ =抹 10 Empirical evidence for the L2 Mandarin word recognition model • Disyllabic word transcription task (Chu & Taft, ISB 2011) 魔鬼 ‘ghost’ – Correct pronunciation: mo2gui3 – Mispronunciation: mo1gui3 (nonword 摸鬼) 11 Conclusion • Three-route L2 word production and recognition model: – Concept, lexical and sublexical • Beginning learners – Use sublexical route in both L2 word production and recognition • Advanced learners – Shift from sublexical to lexical/concept route in L2 word production – Use both sublexical and lexical/concept route in L2 word recognition • Future research – Lexical decision with cross-modal priming – Eye-tracking paradigm with visual-world paradigm – Event-related potential (ERP) 12
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