博碩士論文 108825010 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:48 、訪客IP:18.226.28.197
姓名 張婷予(Ting-Yu Chang)  查詢紙本館藏   畢業系所 認知與神經科學研究所
論文名稱 語境多樣性與語意多樣性對中文字詞辨識影響之事件相關電位研究
(The Effects of Contextual Diversity and Semantic Diversity in Chinese Word Recognition: an ERP study)
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 (2027-1-1以後開放)
摘要(中) 詞頻效果是語言習得研究中最穩定的現象,並用以支持訊息累積的觀點。亦即經驗值增加,是建立詞彙表徵的關鍵因素。但近期研究指出,詞頻對詞彙習得的助益,主要來自於高頻詞更容易出現在不同的文本中(語境多樣性)。而語境多樣性反映的是單純的經驗累積,還是不同文本語境的語意變異,仍有爭議。另有研究使用潛在語義分析方法來計算語意多樣性,以分離語言經驗值與文本中的語意變化。然而語境多樣性與語意多樣性高度相關,其對詞彙學習的影響本質有待釐清。因此本研究使用事件相關電位探討語境多樣性與語意多樣性如何影響中文詞彙辨識的本質。實驗一操弄雙字詞的語境多樣性與語意多樣性,邀請大學生進行具體性判斷作業,其中具體詞與抽象詞各半,分析語境多樣性、語意多樣性與具體性對N400振幅的影響。結果發現具體性與語意多樣性有交互作用,語意多樣性效果僅在抽象詞中被觀察到,語意多樣性愈高,N400愈往負向,因此支持事件基礎理論框架對詞彙表徵建立的看法,亦即詞彙特性與語境的語意變化度皆很重要。然而實驗一並未發現語境多樣性效果,有可能因為語境多樣性和語意多樣性有顯著相關,或是年輕人累積的語言經驗中,語境多樣性的差異無法彰顯。因此實驗二以健康長者為受試者,並調查其閱讀經驗,結果發現具體性、語境多樣性和語意多樣性三者具交互作用,而且老年人的閱讀時間也有影響。在具體詞上,高語境多樣性或是閱讀時間多時,語意多樣性愈高,N400愈往正向。綜合結果支持語境多樣性反映熟悉度,語意多樣性則反映語境意義的變化程度。而詞彙的具體性,也對這兩項指標有不同的影響程度。
摘要(英) Word frequency has been a well-established effect in word acquisition to support the information accumulation perspective. Recent studies indicated that at least part of the word frequency effect is caused by high-frequency words being experienced in more contexts (contextual diversity, CD). However, it is unclear whether contextual diversity is just another index to reflect the accumulation of linguistic experience or the semantic variation across contexts. Thus, researchers also used latent semantic analysis to measure semantic diversity (SD). This study used the event-related potentials (ERPs) to investigate the nature of CD and SD in Chinese word recognition. Experiment 1 invited college students to perform the concreteness judgment task on 280 Chinese two-character words that varied in CD, SD, and concreteness. The single-trial analysis and linear mixed model for statistical analysis were applied to evaluate how these factors modulate the N400 amplitude. The results showed a significant interaction between concreteness and SD. As SD increased, the amplitude of N400 was more negative in reading abstract words. However, there was no CD effect. These findings support the instance-based theoretical framework that the concreteness of a word and the variations of contexts are also crucial for a word’s lexical quality. However, the absence of the CD effect in young adults may be due to the high correlation between CD and SD and their insufficient linguistic experience to reveal the CD effect. Thus, Experiment 2 conducted the same experiment on healthy old adults and also conducted their reading experience by questionnaire. The results showed significant three-way interactions. The SD effect, namely the increased SD elicited more positive N400, was significant in reading concrete words with HCD and for elders with more reading experience. In conclusion, our findings support that CD mainly reflects the word familiarity based on information accumulation while SD reflects the semantic variation across contexts. The multiple exposures of a word in diverse and meaningful language environments are crucial for word leaning, especially for abstract words.
關鍵字(中) ★ 語境多樣性
★ 語意多樣性
★ 具體性
★ 語言經驗
★ N400
關鍵字(英) ★ contextual diversity
★ semantic diversity
★ concreteness
★ linguistic experience
★ N400
論文目次 摘要 i
ABSTRACT ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 viii
一、 緒論 1
1-1 前言 1
1-2 文獻回顧 1
1-2-1 詞彙熟悉度 1
1-2-2 語境語意相異度 4
1-2-3 訊息累積觀點(The information accumulation perspective) 10
1-2-4 事件基礎理論框架(The instance-based theoretical framework) 14
1-2-5 事件相關電位 16
1-3 研究問題與目的 20
1-4 研究假設 21
1-5 研究設計 21
二、 實驗一 23
2-1 研究內容與方法 23
2-1-1 研究對象 23
2-1-2 實驗設計與材料 23
2-1-3 實驗程序 29
2-1-4 腦波紀錄與處理 31
2-1-5 統計分析 32
2-2 研究結果 34
2-2-1 行為反應結果 34
2-2-2 腦波資料結果 36
2-3 討論 39
三、 實驗二 42
3-1 研究內容與方法 42
3-1-1 研究對象 42
3-1-2 實驗設計與材料 42
3-1-3 實驗程序 45
3-1-4 腦波紀錄與處理 45
3-1-5 統計分析 45
3-2 研究結果 48
3-2-1 行為反應結果 48
3-2-2 腦波資料結果 50
3-3 討論 64
四、 綜合討論 68
五、 結論 73
參考文獻 74
附錄一、刺激材料──280個雙字詞 80
附錄二、中文單字讀音造詞測驗 81
附錄三、閱讀習慣問卷 82
參考文獻 Adelman, J. S., Brown, G. D., & Quesada, J. F. (2006). Contextual diversity, not word frequency, determines word-naming and lexical decision times. Psychol Sci, 17(9), 814-823. https://doi.org/10.1111/j.1467-9280.2006.01787.x
Armstrong, B. C., & Plaut, D. C. (2016). Disparate semantic ambiguity effects from semantic processing dynamics rather than qualitative task differences. Language, Cognition and Neuroscience, 31(7), 940-966. https://doi.org/10.1080/23273798.2016.1171366
Balota, D. A., Cortese, M. J., Sergent-Marshall, S. D., Spieler, D. H., & Yap, M. J. (2004). Visual word recognition of single-syllable words. Journal of experimental psychology: General, 133(2), 283.
Barber, H. A., Otten, L. J., Kousta, S.-T., & Vigliocco, G. (2013). Concreteness in word processing: ERP and behavioral effects in a lexical decision task. Brain and language, 125(1), 47-53.
Barsalou, L. W., & Wiemer-Hastings, K. (2005). Situating abstract concepts. In Grounding cognition: The role of perception and action in memory, language, and thought (pp. 129-163). https://doi.org/10.1017/CBO9780511499968.007
Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014). Fitting linear mixed-effects models using lme4. arXiv preprint arXiv, 1406.5823.
Bentin, S., McCarthy, G., & Wood, C. C. (1985). Event-related potentials, lexical decision and semantic priming. Electroencephalography and clinical Neurophysiology, 60(4), 343-355.
Bentin, S., Mouchetant-Rostaing, Y., Giard, M.-H., Echallier, J.-F., & Pernier, J. (1999). ERP manifestations of processing printed words at different psycholinguistic levels: time course and scalp distribution. Journal of Cognitive Neuroscience, 11(3), 235-260.
Besson, M., Kutas, M., & Petten, C. V. (1992). An event-related potential (ERP) analysis of semantic congruity and repetition effects in sentences. Journal of Cognitive Neuroscience, 4(2), 132-149.
Bolger, D. J., Balass, M., Landen, E., & Perfetti, C. A. (2008). Context Variation and Definitions in Learning the Meanings of Words: An Instance-Based Learning Approach. Discourse Processes, 45(2), 122-159. https://doi.org/10.1080/01638530701792826
Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior research methods, 41(4), 977-990.
Brysbaert, M., Stevens, M., Mandera, P., & Keuleers, E. (2016). How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant′s Age. Front Psychol, 7, 1116. https://doi.org/10.3389/fpsyg.2016.01116
Cai, Q., & Brysbaert, M. (2010). SUBTLEX-CH: Chinese word and character frequencies based on film subtitles. PloS one, 5(6), e10729.
Cevoli, B., Watkins, C., & Rastle, K. (2021). What is semantic diversity and why does it facilitate visual word recognition? Behav Res Methods, 53(1), 247-263. https://doi.org/10.3758/s13428-020-01440-1
Chan, K. Y., & Vitevitch, M. S. (2009). The influence of the phonological neighborhood clustering coefficient on spoken word recognition. J Exp Psychol Hum Percept Perform, 35(6), 1934-1949. https://doi.org/10.1037/a0016902
Chapman, C. A., & Martin, R. C. (2021). Effects of semantic diversity and word frequency on single word processing. J Exp Psychol Gen. https://doi.org/10.1037/xge0001123
Chapman, R. M., & Bragdon, H. R. (1964). Evoked responses to numerical and non-numerical visual stimuli while problem solving. nature, 203(4950), 1155-1157.
Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: a dual route cascaded model of visual word recognition and reading aloud. Psychological review, 108(1), 204.
Davis, C. J. (2010). The spatial coding model of visual word identification. Psychological review, 117(3), 713.
Davis, P. A. (1939). Effects of acoustic stimuli on the waking human brain. Journal of neurophysiology, 2(6), 494-499.
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal of psychiatric research, 12(3), 189-198.
Forster, K. I., & Chambers, S. M. (1973). Lexical access and naming time. Journal of Verbal Learning and Verbal Behavior, 12(6), 627-635.
Galbraith, R. C., & Underwood, B. J. (1973). Perceived frequency of concrete and abstract words. Mem Cognit, 1(1), 56-60. https://doi.org/10.3758/BF03198068
Goldstein, R., & Vitevitch, M. S. (2014). The influence of clustering coefficient on word-learning: how groups of similar sounding words facilitate acquisition. Front Psychol, 5, 1307. https://doi.org/10.3389/fpsyg.2014.01307
Grainger, J., & Jacobs, A. M. (1996). Orthographic processing in visual word recognition: a multiple read-out model. Psychological review, 103(3), 518.
Hoffman, P., Lambon Ralph, M. A., & Rogers, T. T. (2013). Semantic diversity: a measure of semantic ambiguity based on variability in the contextual usage of words. Behav Res Methods, 45(3), 718-730. https://doi.org/10.3758/s13428-012-0278-x
Hoffman, P., Ralph, M. L., & Rogers, T. (2021). Semantic diversity is best measured with unscaled vectors: Reply to Cevoli, Watkins and Rastle (2020).
Hoffman, P., & Woollams, A. M. (2015). Opposing effects of semantic diversity in lexical and semantic relatedness decisions. J Exp Psychol Hum Percept Perform, 41(2), 385-402. https://doi.org/10.1037/a0038995
Holcomb, P. J., & Grainger, J. (2006). On the time course of visual word recognition: an event-related potential investigation using masked repetition priming. J Cogn Neurosci, 18(10), 1631-1643. https://doi.org/10.1162/jocn.2006.18.10.1631
Hollis, G. (2020). Delineating linguistic contexts, and the validity of context diversity as a measure of a word′s contextual variability. Journal of Memory and Language, 114. https://doi.org/10.1016/j.jml.2020.104146
Howes, D. H., & Solomon, R. L. (1951). Visual duration threshold as a function of word-probability. Journal of experimental psychology, 41(6), 401.
Hsiao, Y., & Nation, K. (2018). Semantic diversity, frequency and the development of lexical quality in children’s word reading. Journal of Memory and Language, 103, 114-126. https://doi.org/10.1016/j.jml.2018.08.005
Hsu, C.-H., Lee, C.-Y., & Liang, W.-K. (2016). An improved method for measuring mismatch negativity using ensemble empirical mode decomposition. Journal of neuroscience methods, 264, 78-85.
Hsu, C. H., Tsai, J. L., Lee, C. Y., & Tzeng, O. J. (2009). Orthographic combinability and phonological consistency effects in reading Chinese phonograms: an event-related potential study. Brain Lang, 108(1), 56-66. https://doi.org/10.1016/j.bandl.2008.09.002
Hua, M. S., Chang, B. S., Lin, K. N., Yang, C. M., Lu, H. J., & Chen, H. Y. (2005). Wechsler Memory Scale- III (Chinese Version): Administration and Scoring Manual. Chinese Behavioral Science Corporation.
Johns, B. T., Dye, M., & Jones, M. N. (2016). The influence of contextual diversity on word learning. Psychon Bull Rev, 23(4), 1214-1220. https://doi.org/10.3758/s13423-015-0980-7
Johns, B. T., Gruenenfelder, T. M., Pisoni, D. B., & Jones, M. N. (2012). Effects of word frequency, contextual diversity, and semantic distinctiveness on spoken word recognition. J Acoust Soc Am, 132(2), EL74-80. https://doi.org/10.1121/1.4731641
Johns, B. T., Sheppard, C. L., Jones, M. N., & Taler, V. (2016). The Role of Semantic Diversity in Word Recognition across Aging and Bilingualism. Front Psychol, 7, 703. https://doi.org/10.3389/fpsyg.2016.00703
Jones, M. N., Dye, M., & Johns, B. T. (2017). Context as an Organizing Principle of the Lexicon. In (pp. 239-283). https://doi.org/10.1016/bs.plm.2017.03.008
Jones, M. N., Johns, B. T., & Recchia, G. (2012). The role of semantic diversity in lexical organization. Can J Exp Psychol, 66(2), 115-124. https://doi.org/10.1037/a0026727
Kunzetsova, A., Brockhoff, P., & Christensen, R. (2017). lmerTest package: tests in linear mixed effect models. Journal of statistical software, 82(1), 1-26.
Kutas, M., & Federmeier, K. D. (2011). Thirty years and counting: finding meaning in the N400 component of the event-related brain potential (ERP). Annu Rev Psychol, 62, 621-647. https://doi.org/10.1146/annurev.psych.093008.131123
Kutas, M., & Hillyard, S. A. (1980). Reading senseless sentences: Brain potentials reflect semantic incongruity. Science, 207(4427), 203-205.
Kutas, M., & Hillyard, S. A. (1984). Brain potentials during reading reflect word expectancy and semantic association. nature, 307(5947), 161-163. https://doi.org/10.1038/307161a0
Laszlo, S., & Federmeier, K. D. (2011). The N400 as a snapshot of interactive processing: Evidence from regression analyses of orthographic neighbor and lexical associate effects. Psychophysiology, 48(2), 176-186. https://doi.org/10.1111/j.1469-8986.2010.01058.x
Lee, C.-L., & Federmeier, K. D. J. B. R. (2006). To mind the mind: An event-related potential study of word class and semantic ambiguity. 1081(1), 191-202.
Mak, M. H., Hsiao, Y., & Nation, K. (2021). Anchoring and contextual variation in the early stages of incidental word learning during reading. Journal of Memory and Language, 118, 104203. https://doi.org/10.31219/osf.io/kf96e
MATLAB. (2014). version 8.4.0.150421 (R2014b), Natick, Massachusetts: The MathWorks Inc.
Mestres-Missé, A., Münte, T. F., & Rodriguez-Fornells, A. (2014). Mapping concrete and abstract meanings to new words using verbal contexts. Second Language Research, 30(2), 191-223. https://doi.org/10.1177/0267658313512668
Mkrtychian, N., Blagovechtchenski, E., Kurmakaeva, D., Gnedykh, D., Kostromina, S., & Shtyrov, Y. (2019). Concrete vs. Abstract Semantics: From Mental Representations to Functional Brain Mapping. Front Hum Neurosci, 13, 267. https://doi.org/10.3389/fnhum.2019.00267
Monsch, A. U., Bondi, M. W., Butters, N., Salmon, D. P., Katzman, R., & Thal, L. J. (1992). Comparisons of verbal fluency tasks in the detection of dementia of the Alzheimer type. Arch Neurol, 49(12), 1253-1258. https://doi.org/10.1001/archneur.1992.00530360051017
Morton, J. (1969). Interaction of information in word recognition. Psychological review, 76(2), 165.
Nelson, D. L., Bennett, D. J., Gee, N. R., Schreiber, T. A., & McKinney, V. M. (1993). Implicit memory: effects of network size and interconnectivity on cued recall. Journal of Experimental Psychology: Learning, Memory, and Cognition, 19(4), 747.
Noppeney, U., & Price, C. J. (2004). Retrieval of abstract semantics. Neuroimage, 22(1), 164-170. https://doi.org/10.1016/j.neuroimage.2003.12.010
Pagán, A., & Nation, K. (2019). Learning Words Via Reading: Contextual Diversity, Spacing, and Retrieval Effects in Adults. Cogn Sci, 43(1). https://doi.org/10.1111/cogs.12705
Perea, M., Soares, A. P., & Comesana, M. (2013). Contextual diversity is a main determinant of word identification times in young readers. J Exp Child Psychol, 116(1), 37-44. https://doi.org/10.1016/j.jecp.2012.10.014
Pexman, P. M., Heard, A., Lloyd, E., & Yap, M. J. (2017). The Calgary semantic decision project: concrete/abstract decision data for 10,000 English words. Behav Res Methods, 49(2), 407-417. https://doi.org/10.3758/s13428-016-0720-6
Pigada, M., & Schmitt, N. (2006). Vocabulary acquisition from extensive reading: A case study. Reading in a foreign language, 18(1), 1-28.
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. (1996). Understanding normal and impaired word reading: computational principles in quasi-regular domains. Psychological review, 103(1), 56.
Plummer, P., Perea, M., & Rayner, K. (2014). The influence of contextual diversity on eye movements in reading. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(1), 275.
Qiu, M., & Johns, B. T. (2020). Semantic diversity in paired-associate learning: Further evidence for the information accumulation perspective of cognitive aging. Psychon Bull Rev, 27(1), 114-121. https://doi.org/10.3758/s13423-019-01691-w
R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/
Ramscar, M., Hendrix, P., Shaoul, C., Milin, P., & Baayen, H. (2014). The myth of cognitive decline: non-linear dynamics of lifelong learning. Top Cogn Sci, 6(1), 5-42. https://doi.org/10.1111/tops.12078
Rayner, K., & Duffy, S. A. (1986). Lexical complexity and fixation times in reading: Effects of word frequency, verb complexity, and lexical ambiguity. Memory & cognition, 14(3), 191-201.
Reichle, E. D., Pollatsek, A., Fisher, D. L., & Rayner, K. (1998). Toward a model of eye movement control in reading. Psychological review, 105(1), 125.
Rodd, J., Gaskell, G., & Marslen-Wilson, W. (2002). Making Sense of Semantic Ambiguity: Semantic Competition in Lexical Access. Journal of Memory and Language, 46(2), 245-266. https://doi.org/10.1006/jmla.2001.2810
Rubenstein, H., Garfield, L., & Millikan, J. A. (1970). Homographic entries in the internal lexicon. Journal of verbal learning verbal behavior, 9(5), 487-494.
Schmitt, N., & Schmitt, D. (2020). Vocabulary in language teaching. Cambridge university press.
Schwanenflugel, P. J., & Stowe, R. W. (1989). Context Availability and the Processing of Abstract and Concrete Words in Sentences. Reading Research Quarterly, 24(1), 114-126. https://doi.org/10.2307/748013
Segui, J., Mehler, J., Frauenfelder, U., & Morton, J. (1982). The word frequency effect and lexical access. Neuropsychologia, 20(6), 615-627.
Sutton, S., Braren, M., Zubin, J., & John, E. (1965). Evoked-potential correlates of stimulus uncertainty. Science, 150(3700), 1187-1188.
Tsai, P. S., Yu, B. H., Lee, C. Y., Tzeng, O. J., Hung, D. L., & Wu, D. H. (2009). An event-related potential study of the concreteness effect between Chinese nouns and verbs. Brain Res, 1253, 149-160. https://doi.org/10.1016/j.brainres.2008.10.080
Van Petten, C., & Kutas, M. (1990). Interactions between sentence context and word frequency in event-related brain potentials. Memory & cognition, 18(4), 380-393.
Van Petten, C., & Luka, B. J. (2012). Prediction during language comprehension: benefits, costs, and ERP components. Int J Psychophysiol, 83(2), 176-190. https://doi.org/10.1016/j.ijpsycho.2011.09.015
Vergara-Martinez, M., Comesana, M., & Perea, M. (2017). The ERP signature of the contextual diversity effect in visual word recognition. Cogn Affect Behav Neurosci, 17(3), 461-474. https://doi.org/10.3758/s13415-016-0491-7
Verkoeijen, P. P., Rikers, R. M., & Schmidt, H. G. (2004). Detrimental influence of contextual change on spacing effects in free recall. Journal of Experimental Psychology: Learning, Memory, Cognition, 30(4), 796.
Walter, W. G., Cooper, R., Aldridge, V., McCallum, W., & Winter, A. (1964). Contingent negative variation: an electric sign of sensori-motor association and expectancy in the human brain. nature, 203(4943), 380-384.
Webb, S. (2007). The Effects of Repetition on Vocabulary Knowledge. Applied Linguistics, 28(1), 46-65. https://doi.org/10.1093/applin/aml048
West, W. C., & Holcomb, P. J. (2000). Imaginal, semantic, and surface-level processing of concrete and abstract words: an electrophysiological investigation. J Cogn Neurosci, 12(6), 1024-1037. https://doi.org/10.1162/08989290051137558
Wulff, D. U., De Deyne, S., Jones, M. N., Mata, R., & Aging Lexicon, C. (2019). New Perspectives on the Aging Lexicon. Trends Cogn Sci, 23(8), 686-698. https://doi.org/10.1016/j.tics.2019.05.003
Yap, M. J., Lim, G. Y., & Pexman, P. M. (2015). Semantic richness effects in lexical decision: The role of feedback. Mem Cognit, 43(8), 1148-1167. https://doi.org/10.3758/s13421-015-0536-0
指導教授 李佳穎 徐峻賢(Chia-Ying Lee Chun-Hsien Hsu) 審核日期 2022-4-27
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明