1南京师范大学文学院, 南京 210097
2纽约州立大学奥尔巴尼分校教育学院, 纽约 12222
3南京师范大学心理学院, 南京 210097
收稿日期:
2020-06-28出版日期:
2021-05-15发布日期:
2021-03-30通讯作者:
梁丹丹E-mail:ldd233@163.com基金资助:
江苏省社会科学基金项目成果(19YYC003);江苏高校优势学科建设工程资助项目(PAPD)The influence of linguistic experience on statistical word segmentation
YU Wenbo1, WANG Lu1, CHENG Xingyue1, WANG Tianlin2, ZHANG Jingjing3, LIANG Dandan1()1School of Chinese Language and Culture, Nanjing Normal University, Nanjing 210097, China
2School of Education, University at Albany, State University of New York, New York 12222, USA
3School of Psychology, Nanjing Normal University, Nanjing 210097, China
Received:
2020-06-28Online:
2021-05-15Published:
2021-03-30Contact:
LIANG Dandan E-mail:ldd233@163.com摘要/Abstract
摘要: 概率词切分指个体利用音节间的转换概率切分语流、发现词语边界的过程。经典的概率词切分研究多采用“学习-测试”范式, 首先要求被试切分一段无意义人工语言, 随后对切分效果进行测试。近年来, 研究者逐渐关注语言经验对概率词切分的影响, 具体包括语音经验和被试掌握的语言知识两方面。今后的研究, 一方面可以更多地关注普通话母语者的语言经验如何作用于概率词切分过程; 另一方面还可以在语言经验的分类上进行拓展, 细分群体语言经验和个体语言经验的影响。
图/表 1
图1索绪尔对口语词切分的观点 (资料来源:de Saussure & Baskin, 1916)
图1索绪尔对口语词切分的观点 (资料来源:de Saussure & Baskin, 1916)
参考文献 59
[1] | 冯胜利. (1998). 论汉语的 “自然音步”. 中国语文, (1),40-47. |
[2] | 李斌, 刘雪扬. (2018). 基于《汉语大词典》的汉语词汇历时演变计量研究. 南京师大学报(社会科学版), (5),152-160. |
[3] | 李利, 李亚娴, 康宇, 王莉. (2020). 声调语言经验在汉语二语者普通话声调感知中的作用. 华南师范大学学报(社会科学版), (1),83-91. |
[4] | 廖毅, 张薇. (2019). 母语背景在汉语声调感知中的影响——以英语和粤语背景学习者为例. 汉语学习, (1),75-86. |
[5] | 林焘, 王理嘉. (1992). 语音学教程. 北京: 北京大学出版社. |
[6] | 王婷, 王丹, 张积家, 崔健爱. (2017). “各说各话”的语言经验对景颇族大学生执行功能的影响. 心理学报, 49(11),1392-1403. |
[7] | 于文勃, 梁丹丹. (2018). 口语加工中的词语切分线索. 心理科学进展, 26(10),1765-1774. |
[8] | 张珊珊, 杨亦鸣. (2012). 从记忆编码加工看人脑中的基本语言单位——一项基于单音节语言单位的ERPs研究. 外语与外语教学, (2),1-6. |
[9] | Antovich, D. M., & Estes, K. G. (2017). Learning across languages: Bilingual experience supports dual language statistical word segmentation. Developmental Science, 21(2),e12548. doi: 10.1111/desc.12548. doi: 10.1111/desc.12548URL |
[10] | Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language, 59(4),390-412. doi: 10.1016/j.jml.2007.12.005URL |
[11] | Batterink, L. J. (2017). Rapid statistical learning supporting word extraction from continuous speech. Psychological Science, 28(7),921-928. doi: 10.1177/0956797617698226URLpmid: 28493810 |
[12] | Batterink, L. J., Reber, P. J., Neville, H. J., & Paller, K. A. (2015). Implicit and explicit contributions to statistical learning. Journal of Memory and Language, 83,62-78. doi: 10.1016/j.jml.2015.04.004URLpmid: 26034344 |
[13] | Batterink, L. J., & Paller, K. A. (2017). Online neural monitoring of statistical learning. Cortex, 90,31-45. URLpmid: 28324696 |
[14] | Bogaerts, L., Siegelman, N., & Frost, R. (2016). Splitting the variance of statistical learning performance: A parametric investigation of exposure duration and transitional probabilities. Psychonomic Bulletin & Review, 23(4),1250-1256. URLpmid: 26743060 |
[15] | Bonatti, L. L., Pe?a, M., Nespor, M., & Mehler, J. (2005). Linguistic constraints on statistical computations: The role of consonants and vowels in continuous speech processing. Psychological Science, 16(6),451-459. doi: 10.1111/j.0956-7976.2005.01556.xURLpmid: 15943671 |
[16] | Bortfeld, H., Morgan, J. L., Golinkoff, R. M., & Rathbun, K. (2005). Mommy and me: familiar names help launch babies into speech-stream segmentation. Psychological Science, 16(4),298-304. doi: 10.1111/j.0956-7976.2005.01531.xURLpmid: 15828977 |
[17] | Bosseler, A. N., Teinonen, T., Tervaniemi, M., & Huotilainen, M. (2016). Infant directed speech enhances statistical learning in newborn infants: An ERP study. PLoS ONE, 11(9),e0162177. doi: 10.1371/journal.pone.0162177. URLpmid: 27617967 |
[18] | Buiatti, M., Pe?a, M., & Dehaene-Lambertz, G. (2009). Investigating the neural correlates of continuous speech computation with frequency-tagged neuroelectric responses. NeuroImage, 44(2),509-519. URLpmid: 18929668 |
[19] | Cutler, A., & Norris, D. (1988). The role of strong syllables in segmentation for lexical access. Journal of Experimental Psychology: Human Perception and Performance, 14(1),113-121. doi: 10.1037/0096-1523.14.1.113URL |
[20] | de Saussure, F., & Baskin, W. (1916). Course in general linguistics. London, UK: Duckworth. |
[21] | Ding, N., Melloni, L., Zhang, H., Tian, X., & Poeppel, D. (2016). Cortical tracking of hierarchical linguistic structures in connected speech. Nature Neuroscience, 19(1),158-164. doi: 10.1038/nn.4186URLpmid: 26642090 |
[22] | Emberson, L. L., Misyak, J. B., Schwade, J. A., Christiansen, M. H., & Goldstein, M. H. (2019). Comparing statistical learning across perceptual modalities in infancy: An investigation of underlying learning mechanism (s). Developmental Science, 22(6),e12847. doi: 10.1111/ DESC.12847. doi: 10.1111/desc.12847URLpmid: 31077516 |
[23] | Endress, A. D., & Langus, A. (2017). Transitional probabilities count more than frequency, but might not be used for memorization. Cognitive Psychology, 92,37-64. doi: 10.1016/j.cogpsych.2016.11.004URLpmid: 27907807 |
[24] | Erickson, L. C., Kaschak, M. P., Thiessen, E. D., & Berry, C. A. S. (2016). Individual differences in statistical learning: Conceptual and measurement issues. Collabra: Psychology, 2(1),14. doi: 10.1525/ collabra.41. |
[25] | Erickson, L. C., Thiessen, E. D., & Estes, K. G. (2014). Statistically coherent labels facilitate categorization in 8-month-olds. Journal of Memory and Language, 72,49-58. doi: 10.1016/j.jml.2014.01.002URL |
[26] | Estes, K. G., Evans, J. L., Alibali, M. W., & Saffran, J. R. (2007). Can infants map meaning to newly segmented words? Statistical segmentation and word learning. Psychological Science, 18(3),254-260. URLpmid: 17444923 |
[27] | Estes, K. G., Gluck, C. W., & Bastos, C. (2015). Flexibility in statistical word segmentation: Finding words in foreign speech. Language Learning and Development, 11(3),252- 269. |
[28] | Estes, K. G., & Lew-Williams, C. (2015). Listening through voices: Infant statistical word segmentation across multiple speakers. Developmental Psychology, 51(11),1517-1528. doi: 10.1037/a0039725URLpmid: 26389607 |
[29] | Franco, A., Eberlen, J., Destrebecqz, A., Cleeremans, A., & Bertels, J. (2015). Rapid serial auditory presentation: A new measure of statistical learning in speech segmentation. Experimental Psychology, 62,346-351. doi: 10.1027/1618-3169/a000295URLpmid: 26592534 |
[30] | Frost, R., Armstrong, B. C., & Christiansen, M. H. (2020). Statistical learning research: A critical review and possible new directions. Psychological Bulletin, 145(12),1128-1153. doi: 10.1037/bul0000210URLpmid: 31580089 |
[31] | Frost, R. L. A., Monaghan, P., & Christiansen, M. H. (2019). Mark my words: High frequency marker words impact early stages of language learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(10),1883-1898. URLpmid: 30652894 |
[32] | Gómez, D. M., Mok, P., Ordin, M., Mehler, J., & Nespor, M. (2017). Statistical speech segmentation in tone languages: The role of lexical tones. Language & Speech, 61(1),84-96. URLpmid: 28486862 |
[33] | Gout, A., Christophe, A., & Morgan, J. L. (2004). Phonological phrase boundaries constrain lexical access II. Infant data. Journal of Memory and Language, 51(4),548-567. doi: 10.1016/j.jml.2004.07.002URL |
[34] | Gout, A., Christophe, A., & Morgan, J. L. (2004). Phonological phrase boundaries constrain lexical access II. Infant data. Journal of Memory and Language, 51(4),548-567. doi: 10.1016/j.jml.2004.07.002URL |
[35] | Hoch, L., Tyler, M. D., & Tillmann, B. (2013). Regularity of unit length boosts statistical learning in verbal and nonverbal artificial languages. Psychonomic Bulletin & Review, 20(1),142-147. URLpmid: 22890871 |
[36] | Johnson, E. K., & Tyler, M. D. (2010). Testing the limits of statistical learning for word segmentation. Development Science, 13(2),339-345. doi: 10.1111/desc.2010.13.issue-2URL |
[37] | Kurumada, C., Meylan, S. C., & Frank, M. C. (2011). Zipfian word frequencies support statistical word segmentation. Proceedings of the Annual Meeting of the Cognitive Science Society, 33,2667-2672.Retrieved from https:// escholarship.org/uc/item/58j0m9rq. |
[38] | Lew-Williams, C., & Saffran, J. R. (2012). All words are not created equal: Expectations about word length guide infant statistical learning. Cognition, 122(2),241-246. URLpmid: 22088408 |
[39] | Li, M., Xu, Y., Luo, X., Zeng, J., & Han, Z. (2020). Linguistic experience acquisition for novel stimuli selectively activates the neural network of the visual word form area. NeuroImage, 215. doi: 10.1016/j.neuroimage. 2020.116838. doi: 10.1016/j.neuroimage.2020.116841URLpmid: 32283274 |
[40] | Magezi, D. A. (2015). Linear mixed-effects models for within-participant psychology experiments: An introductory tutorial and free, graphical user interface (LMMgui). Frontiers in Psychology, 6. doi: 10.3389/FPSYG.2015. 00002. doi: 10.3389/fpsyg.2015.02034URLpmid: 26834666 |
[41] | McQueen, J. M. (1998). Segmentation of continuous speech using phonotactics. Journal of Memory and Language, 39(1),21-46. |
[42] | Nazzi, T., Dilley, L. C., Jusczyk, A. M., Shattuck-Hufnagel, S., & Jusczyk, P. W. (2005). English-learning infants’ segmentation of verbs from fluent speech. Language and Speech, 48(3),279-298. |
[43] | Onnis, L., & Thiessen, E. D. (2013). Language experience changes subsequent learning. Cognition, 126(2),268-284. URLpmid: 23200510 |
[44] | Palmer, S. D., Hutson, J., White, L., & Mattys, S. L. (2019). Lexical knowledge boosts statistically-driven speech segmentation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(1),139-146. |
[45] | Palmer, S. D., & Mattys, S. L. (2016). Speech segmentation by statistical learning is supported by domain-general processes within working memory. The Quarterly Journal of Experimental Psychology, 69(12),2390-2401. doi: 10.1080/17470218.2015.1112825URLpmid: 27167308 |
[46] | Potter, C. E., Wang, T., & Saffran, J. R. (2017). Second language experience facilitates statistical learning of novel linguistic materials. Cognitive Science, 41(S4),913-927. |
[47] | Poulin-Charronnat, B., Perruchet, P., Tillmann, B., & Peereman, R. (2016). Familiar units prevail over statistical cues in word segmentation. Psychological Research, 81,990-1003. doi: 10.1007/s00426-016-0793-yURLpmid: 27580733 |
[48] | Saffran, J. R., Aslin, R. N., & Newport, E. L. (1996). Statistical learning by 8-month-old infants. Science, 274(5294),1926-1928. URLpmid: 8943209 |
[49] | Saffran, J. R., & Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69(1),181-203. |
[50] | Sanders, L. D., Newport, E. L., & Neville, H. J. (2002). Segmenting nonsense: An event-related potential index of perceived onsets in continuous speech. Nature Neuroscience, 5(7),700-703. doi: 10.1038/nn873URLpmid: 12068301 |
[51] | Schad, D. J., Vasishth, S., Hohenstein, S., & Kliegl, R. (2020). How to capitalize on a priori contrasts in linear (mixed) models: A tutorial. Journal of Memory and Language, 110. doi: 10.1016/j.jml.2019.104038. URLpmid: 33100506 |
[52] | Shoaib, A., Wang, T., Hay, J. F., & Lany, J. (2018). Do infants learn words from statistics? Evidence from English-learning infants hearing Italian. Cognitive Science, 42(8),3083-3099. doi: 10.1111/cogs.12673URLpmid: 30136301 |
[53] | Siegelman, N., Bogaerts, L., Elazar, A., Arciuli, J., & Frost, R. (2018). Linguistic entrenchment: Prior knowledge impacts statistical learning performance. Cognition, 177,198-213. doi: 10.1016/j.cognition.2018.04.011URLpmid: 29705523 |
[54] | Siegelman, N., Bogaerts, L., & Frost, R. (2017). Measuring individual differences in statistical learning: Current pitfalls and possible solutions. Behavior Research Methods, 49(2),418-432. doi: 10.3758/s13428-016-0719-zURLpmid: 26944577 |
[55] | Smith, N. A., & Trainor, L. J. (2008). Infant-directed speech is modulated by infant feedback. Infancy, 13(4),410-420. |
[56] | Suomi, K., McQueen, J. M., & Cutler, A. (1997). Vowel harmony and speech segmentation in Finnish. Journal of Memory and Language, 36(3),422-444. |
[57] | Thiessen, E. D., Hill, E. A., & Saffran, J. R. (2005). Infant-directed speech facilitates word segmentation. Infancy, 7(1),53-71. URLpmid: 33430544 |
[58] | Toro, J. M., Pons, F., Bion, R. A. H., & Sebastián-Gallés, N. (2011). The contribution of language-specific knowledge in the selection of statistically-coherent word candidates. Journal of Memory and Language, 64(2),171-180. |
[59] | Wang, T. L., & Saffran, J. R. (2014). Statistical learning of a tonal language: the influence of bilingualism and previous linguistic experience. Frontiers in Psychology, 5,593. doi: 10.3389/fpsyg.2014.00953. URLpmid: 25071617 |
相关文章 4
[1] | 顾俊娟, 石金富. 汉字位置加工和词边界效应的认知机制[J]. 心理科学进展, 2021, 29(2): 191-201. |
[2] | 白学军;张慢慢;臧传丽;李馨;陈璐;闫国利. 词边界信息在中文词汇学习与识别中的作用:眼动研究的证据[J]. 心理科学进展, 2014, 22(1): 1-8. |
[3] | 丁国盛;李妍妍. 聋人早期手语经验对脑功能及结构的塑造作用[J]. 心理科学进展, 2012, 20(3): 328-337. |
[4] | 李兴珊;刘萍萍;马国杰. 中文阅读中词切分的认知机理述评[J]. 心理科学进展, 2011, 19(4): 459-470. |
PDF全文下载地址:
http://journal.psych.ac.cn/xlkxjz/CN/article/downloadArticleFile.do?attachType=PDF&id=5422