Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg

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1 Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg March 1, 2007 The catalogue is organized into sections of (1) obligatory modules ( Basismodule ) that have to be passed by all students, (2) core modules the students may freely combine for a sum of 32 ECTS credits from these modules, (3) advanced topics (all modules compulsory), (4) auxillary studies (all modules compulsory), (5) modules from their minor and (6) the exam. This catalogue reflects the examination regulation ( Prüfungsordnung ) of November 21, It is a draft. Authoritative information is given in the German Modulkatalog. 1 Obligatory Modules B01 Introduction to Computational Linguistics Introduction to the basics of both linguistics and natural language processing. The profile of computational linguistics. Overview of integrated language processing systems and the corresponding linguistic disciplines and their basics and methods. Overview of informatics. Example applications for each linguistic discipline. Philosophy of science. B02 Programming I: Introduction Fundamentals of programming using a procedural, object-oriented language with particular emphasis on non- and seminumeric problems: elementary and advanced data types and operators, input/output, control structures, functions, object orientation. Also provides insight into functional programming styles, modern error handling, factorization techniques. 1

2 B03 Algorithms and Data Structures 9 ECTS Credits Brief introduction to the disciplines of informatics. Properties and specification of algorithms. E.g.: Turing machines; abstract data type; list, queue, stack; sorting algorithms; set manipulation; elementary search procedures; search trees; hashing algorithms; graph algorithms; text processing; complexity; introduction to computability and program verification. B04 Programming II: Intermediate 5 ECTS Credits Extension of programming skills using a more machine-oriented language (currently C): preprocessors, libraries, development tools (make, debugger, profiler), memory management, efficiency issues, patterns. B05 Foundations of Formal Languages Introduction to the mathematical description of formal languages: tools for formal languages - sets, relations, mappings, graphs; regular, context-free, contextsensitive, recursively enumerable languages; finite automata, pushdown automata, turing machines; elements of computability theory, halting problem. B06 Morphology The study of morphological and morpho-syntactic properties of words. Introduction to relevant paradigms, terminological background. Computational morphology: simple finite-state models, advanced current models (such as two level morphology). Item-and-arrangement, item-and-process, word-and-paradigm. Morphosyntactic classification, morphological features. B07 Lexical Semantics The semantics of words and relationships between them (synonymy, meronymy, etc). Approaches to modelling lexical semantics, component analysis, prototype theory. Methods of lexical analysis, operational criteria for classification. Entries in lexicons, semantic networks, ontologies. Polysemy, lexical collocation. B08 Syntax 5 ECTS Credits Investigation of syntagmatic properties of words. Methods of text analysis, corpus work, heuristics. Syntactic dependency, syntagmatic roles, morpho-syntactic government. Introduction to a grammar formalism concentrating on the lexicon (subcategorization and valency). 2

3 B09 Parsing Systematic overview of the tasks of a computer program for syntactic analysis. Algorithms that tackle these tasks and their alternatives. Overview over prototypical parsers, e.g. recursive-descent parsers, Earley parsers, the Cocke/Kasami/Younger parser, table-controlled shift reduce parsers, finite-state parsers, augmented transition networks, or slot-and-filler parsers for dependency grammars. Efficiency measures. evaluation criteria. B10 Pragmatics and Text Linguistics Introduction to speech act theory, speech act sequences. Conversational postulates. Concepts and methods of discourse structuring on the levels of text and of dialog. Syntagmatic connectivity (cohesion) and pragmatic connectivity (coherence). Coherence in monological texts, implicit question-answer-relations, rhetorical structure theory, cue phrases. Cohesion based on coreference, predicate-based connectivity, contiguity. Relation between text and sentence structure. Information structure: theme-rheme, topic-comment, background-focus. Ways of modelling this information that enable the computer to process natural language dialogue and text, or to produce them. B11 Logic Some mathematical foundations (set theory, algebra). Propositional calculus, first order predicate calculus. 2 Core Modules A01 Course in Computer Science 9 ECTS Credits A course from the Computer Science curriculum chosen at the student s discretion. A02 Software Engineering 9 ECTS Credits Introduction to software engineering, methods of software design, standardised methods for software development, design patterns. Introduction to project management. Software project (supervised). A03 Topics in Programming Courses focusing on specific aspects of the development of software in natural language processing. 3

4 A04 Introduction to Artificial Intelligence Overview over the field of artificial intelligence research and cognitive science. Knowledge representation and engineering. Cognitive models, common sense knowledge, heuristics. Adaptivity and user modelling in interactive software systems. Exemplary applications: applications from NLP, expert systems, robotics, games, etc. A05 Methods of Knowledge-Based Informatics Systematic introduction to established methods of knowledge-based programming and system design. Pattern matching. Planing, search strategies, heuristics. Deduction, induction and abduction, non-monotonic reasoning, fuzzy logic. Connectionist networks. A06 Prolog Introduction to logic programming, with an emphasis on syntax parsing, knowledge representation and inference. Example applications from natural language processing and artificial intelligence. A07 Sentence Semantics Phenomena of sentence semantics (those connected to syntax and syntactic phenomena as opposed to lexical and referential phenomena). Mostly concerned with semantic relations between sentences (such as paraphrase, implication, presupposition). The concept of truth conditional semantics or the logical form of language. Introduction to advanced concepts in logics (modal logics, type theory, lambda expressions etc.). Translation of parts of expressions in natural language into logical language and composition of these translations through suitable operations. Syllogistic approaches, modelling of logical semantics through operations on the syntactic level (cf. transformation grammar). A08 Text Semantics A comprehensive overview of how text meaning is constructed. The course is a sequel to Pragmatics and Text Linguistics and further develops the skills obtained there. The most important computational approaches in the field are also discussed. A09 Formal Grammar An introduction into a modern grammar formalism, e.g., HPSG, LFG, TAG, and its application to linguistic problems. 4

5 A10 Introduction to Quantitative NLP Elementary introduction to statistics for language description and processing: probability theory, descriptive statistics, estimation, testing, entropy, simple Bayesian statistics, hidden Markov models, expectation maximizationon. A11 Information Retrieval A survey of the methods of information retrieval and the role of linguistics in the field. A12 Handling of Large Corpora Application of statistical methods to corpora. Information extraction and text mining. Detection and structuring of relevant information units from a number of unstructured or semi-structured documents, e.g. extraction of terms and ontologies, topic detection, named entity recognition, extraction of templates and classification of documents. Tokenization, lemmatization, tagging, probabilistic parsing, chunking, disambiguation. A14 Text technology Introduction to the various aspects of processing and storing large amounts of textual information, including markup, metadata, classification and retrieval. A15 Computational Lexicography Topics discussed include the stucture of dictionaries and encyclopedias, formalisms for their description and the use of NLP tools for building and maintaining them. A16 Psycholinguistics Introduction to the psychological bases of language reception, production and acquisition. A17 Phonetics Introduction to phonetics. Simple and composite oscillations, resonance and filtering, sound and speech sound. Registration and analysis of speech sound. Acoustic features of different sound groups: vowels, vowel formants, basic forms of consonant sound, specific acoustic properties of different consonants. Voicing of consonants. Linear progression of speech. Overlapping of sounds during the progression of speech. Segmentation, intonation, accent. Difference between speaking and singing voice. 5

6 A18 Speech Recognition Introduction to speech recognition. Processing and classification of speech signals, methods for single word recognition, Hidden Markov Models, recognition of continuous speech, acoustic models, speech models, search methods, adaptation methods, neural networks in speech recognition. Generation of correct orthography. A19 Speech Generation Introduction to speech synthesis. Analysis components, phonetic and prosodic modelling (phonetic transcription with accent and intonation curves). A20 Introduction to Machine Translation Language comparison. Problems of translation. Human translation, machine translation, human-aided machine translation, machine-aided human translation. Transferbased approaches. Interlingua-based approaches. Components of machine translation systems (analysis, transfer, generation). Knowledge-based translation systems. A21 Machine Translation II 3 ECTS Credits Investigation of specific methods or systems in machine translation with specific emphasis on applying skills to the solution of actual problems in MT. 3 Advanced Topics V01 Research Seminar An advanced seminar from the courses offered for the MA level chosen at the student s discretion. V02 Professional Talks Oral presentations by the attendants followed by discussions with particular emphasis on formal aspects of giving talks. V03 Hands-on Project Independent implementation of a running software program tackling a problem from computational linguistics. The problem will usually be inspired by a course that also covers the prerequisites for its proper treatment. 6

7 V04 Conferences and Summer Schools 2 ECTS Credits Attendance of a research conference of at least three days duration, in either Computational Linguistics, Informatics or a neighbouring discipline. 4 Auxillary Studies E01 Technology Assessment 3 ECTS Credits The role of computers and new media in society. Opportunities and dangers of systems that solve cognitive problems. Effects on the job market, work in general, politics, culture, education. Further subjects such as computer crimes, privacy, copyright. E02 Soft Skills A course on soft skills to be chosen at the student s discretion. 2 ECTS Credits E03 Internship 10 ECTS Credits Eight week internship in a company or an institute using or related to information technology, ideally working on natural language processing. 5 Minor NB Obligatory Course in Minor up to 12 ECTS Credits An obligatory course in the minor subject. The contents is dependent on the chosen minor. NA Optional Course in Minor up to 12 ECTS Credits An optional course in the minor subject. The contents is dependent on the chosen minor. 6 Exam BAA Bachelor Thesis 10 ECTS Credits A thesis on a topic in computational linguistics to be written within six weeks. 7

8 BAP Oral Exam 10 ECTS Credits An oral exam of 30 Minutes covering the entire contents of the Bachelor program. The exam has a focus on three modules representative of the subject. 8

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