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In Search of a Measure of Grammaticality: A Probabilistic Approach
Liang Maocheng
In Search of a Measure of Orality:
A Probabilistic Approach
Xu Jiajin
Register Variation: A SP-WR case
Xu JiajinBeijing Foreign Studies University
4
Written language bias
• For decades• Have we gone astray in linguistic
inquiry?
• In the least, equal attention should be given to spoken language.
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• What are the defining features of spoken language?
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Written/literate features
• Long, embedded complete sentences• Relative clauses• Long, nominalised abstract words• Passive voice• etc
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Spoken features
• Incomplete sentences, ellipsis• Questions, interrogative sentences• Tag questions• Inversion, post-posed elements• Contractions• Small, easy everyday words• Interactive, interpersonal, expressive• Hedges, discourse marker use• Fillers, pause markers• Negation (Yes). No.
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Why do they differ?
• According to Wallace Chafe (1982), two factors explain the differences between written discourse and verbal interaction:
• 1) Writing takes longer than speaking;
• 2) Writers do not contact with readers.
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• The first factor is responsible for the very many fragments in SD; and
• the second factor is responsible for the detachment from the readers as opposed to the high involvement in verbal communication.
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Distinctive features b/t speech & writing
• Think about typical written discourse and typical spoken discourse
• Academic writing (research articles)
• Everyday casual conversation (small talk)
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Paper reading and replicate
• Writer/reader visibility in EFL written discourse
• Stephanie Petch-Tyson
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Spoken features of learner writing
• Writer reader visibility
• Petch-Tyson ( 1998)
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Questions for reading
• Research aims
• Data
• Method
• Conclusion
• Critique
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Biber’s MF/MD model
• 67 features (Biber 1988)
• 125 features (Biber 2007)
• 141 features (Xiao 2009)• Features collected in literature and according to
intuition• List of spoken features will never be exhausted.• BFSU_MF_MD tool
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Two overarching approaches
• Rule-based: Sth that we are sure about• Pro and con• - Can never be exhaustive
• - A blind men and elephant matter
• + It’s good enough if we get the best part. • 5万和 3万没有差别
• Probabilistic: Greedy and exhaustive
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A keyword approach to Speech writing difference
Spokencorpus
Writtencorpus
vs
vsSP Word list WR Word list
SP Keywordlist
How a keyword list is generated?
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Task: Keywordcorpus driven approach
• Observed: dem: • Demographically sampled spoken data
• Reference: aca + fic + news
• Probabilistic approach
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Bibliography 1/3
Biber, D. 1988. Variation across Speech and Writing. Cambridge: CUP.Biber, D. et al. 1999. Longman Grammar of Spoken and Written Langua
ge. London: Longman.Brazil, D. 1995. A Grammar of Speech. Oxford: OUP.Cameron, D. 2001. Working with Spoken Discourse. London: SAGE Pub
lications.Carter R. & M. McCarthy. 1997. Exploring Spoken Language. Cambridg
e: CUP.Chafe, W. 1994. Discourse, Consciousness, and Time. Chicago: Univers
ity of Chicago Press.Campoy, M. & M. Luzón. (eds.). 2007. Spoken Corpora in Applied Lingui
stics. Bern: Peter Lang.
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Bibliography 2/3
Cornbleet, S. & R. Carter. 2001. The Language of Speech and Writing. London: Routledge.
Ellis, R. & G. Barkhuizen. 2005. Analyzing Learner Language. Oxford: OUP.
Hughes, E. (ed.). 2006. Spoken English, TESOL and Applied Linguistics. New York: Palgrave.
McCarthy, M. 1998. Spoken Language and Applied Linguistics. Cambridge: CUP.
Muller, S. 2005. Discourse Markers in Native and Non-native English Discourse. Amsterdam: John Benjamins.
Petch-Tyson, S. 1998. Writer/ reader visibility in EFL written discourse. In S. Granger ( ed. ) . Learner English on Computer. 107-118.
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Bibliography 3/3
丁海涛, 2008 , A Keyword Approach to Spoken Features in the English Essays by Chinese non-English Major College Students,中国外语教学研究中心硕士论文。
文秋芳、丁言仁、王文宇, 2003,中国大学生英语书面语中的口语化倾向,《外语教学与研究》( 4): 268-275。
文秋芳, 2009,学习者英语语体特征变化的研究,《外国语》( 4)。吴琼, 2007 , A Register Analysis of Spoken English of Chinese EFL
Learners: A Multi-dimensional Approach(中国英语学习者英语口语语域的多维度研究),中国外语教学研究中心硕士论文。
许家金、许宗瑞, 2007,中国大学生英语口语中的互动话语词块研究,《外语教学与研究》( 6): 437-443。
Thank you
xujiajin