計(jì)算機(jī)語言學(xué)語料庫(kù)語言學(xué)機(jī)器翻譯.pptVIP

Chapter 10 Language and Computer,English Linguistics: An Introduction,Chapter 10 Language and Computer,0. Warm-up Questions 1. Computational Linguistics 2. CALL 3. Machine Translation 4. Corpus Linguistics,0. Warm-up Questions,In what ways can computer facilitate our language learning? To what extent do you rely on computer in your English learning? How to improve the output quality of machine translation? What is the impact of the Internet on machine translation?,1. Computational Linguistics,1.1 Definition (p226),A branch of applied linguistics, dealing with computer processing of human language.,1.2 Related subjects,Programmed instruction 編序教學(xué)法、程式化教學(xué) Speech synthesis 言語合成 Automatic recognition of human speech Automatic translation of natural languages Communication between people and computers Text processing, etc,2. CALL,2.1 CAI, CAL, CALL (p226),CAI: Computer-assisted Instruction CAL: Computer-assisted Learning CALL: Computer-assisted Language Learning,2.2 Phases of CALL,Behavioristic CALL: computer as tutor Communicative CALL: computer as stimulus Integrative CALL: multimedia and the Internet,2. CALL,2.3 Types of CALL programs,Davies & Higgins (1985): Gapmaster, Mazes, etc. Jones & Fortescue (1987): Matchmaster, Wordstore, etc. Higgins (1993): Customizing, Computer networks, etc,2.4 Advantages and Problems,Advantages Motivation, adaptive, authenticity, critical thinking Problems (Limitations of the technology) ability (human-like interaction), availability (cost), etc.,3. Machine Translation,3.1 Introduction,Definition: the use of machine (usually computers) to translate text (or speech) from one natural L to another. Types: Unassisted MT and Assisted MT; T2T MT, S2S MT, S2T MT, T2S MT,3.2 History of development,1950s: independent work by MT researchers 1960s: hope for good quality Since 1970s: computer-based tools,3. Machine Translation,3.3 Research methods,Rule-based: Transfer- & dictionary-based, interlingual Knowledge-based: semantic, pragmatic, real-world Corpus-based: statistical, example-based,3.4 Advantages and Problems,Advantages: cost-effective, time-saving Problems: output quality hard to ensure (reasons?),4. Corpus Linguistics,4.1 Definition (p238),Corpus: a collection of linguistic data, either compiled as written texts or as transcription of recorded speech. Corpus linguistics deals with the principles and practice of using corpora in language study.,4.2 Features of the corpus,Representativeness Finite size Machine-readable form A standard reference,4. Corpus Linguistics,4.3 Types of the corpus (p273),In terms of function, there are four common types of corpora: General corpora: broadly homogeneous Specialized corpora: for specific purposes Sample corpora: genre-based Monitor corpora: gigantic, ever moving store,4. Corpus Linguistics,4.4 For language learning,The corpus can be used to Search for a particular word, sequence of words or even a part of speech in a text; Retrieve all examples of a particular word; Compare the different usages of the same word; Analyse keywords; Analyse word frequencies; Find and analyse phrases and idioms; Create indexes and word lists, etc.,4. Corpus Linguistics,4.4 For language study,Lexical studies: complete and precise definitions and usage of words and phrases. Grammar: The potential for the representative quantification of a whole language variety. Their role as empirical data for the testing of hypotheses derived from