Lists of topics covered in courses and further links.

The EMA topic areas

More about the courses

Theoretical Linguistics top
Lgs-1 SWL1 MORPH SYN1 Sem-1 SYN2 Pragm Comptl. Lxgr.
Basic notions •
Structure of Language •
Morphology and the lexicon •
Inflectional morphology • •
Derivational morphology • •
Structure of the lexicon • • •
Morphological Theory •
Syntax
Context free phrase-structure grammars • •
Evaluating grammars •
Syntactic theory • •
Semantics
Lexical Semantics •
Meaning above the word •
Formal semantics •
Pragmatics
Speech acts •
Conversational implicature •
Grice •
Discourse
Models of discourse structure • •
Information structure •

Natural Language Processing top
ICS ICS-2 LFM-1 LFM-2 Lgs-1 CPL SWL1 MORPH PA1 Sem SYN2 AlSyn Pragm Alg+Datastr. Cp Comptl. Lxgr. SLDS
Introduction
Application of NLP • •
The different analysis levels used for NLP • • •
Markup (TEI, Unicode) •
Finite state automata, transducers • •
Lexical level
Error-tolerant lexical processing •
Design of morphologic analysers •
Part of speech tagging [Brill, HMM] • •
Efficient representation for linguistic resources •
Syntactic level
Grammars • •
Parsing • • • • •
Automated estimation of probabilistic model parameters
Data Oriented Parsing •
Semantic level
Logical forms • • •
Ambiguity resolution • •
Semantic networks •
Semantic parsers • •
Procedural semantics •
Logical semantics • • •
Vector Space semantics
Pragmatic level
Knowledge representation • •
Reasoning
Plan/goal recognition •
Speech acts/intentions • •
Belief models • •
Discourse • •
Reference •
Natural language generation
Content determination
Sentence planning
Surface realisation
Other approaches
Statistical/corpus-based NLP •
Connectionist NLP

Phonetics and Phonology top
IPho SigPro SR-2 SS1 SS2
Speech Production •
Sound Source • •
Articulation •
Coarticulation •
Prosody • • •
Acoustic phonetics •
Fant's source-filter model • •
Experimental methods and tools •
Acoustic properties of speech sounds • •
Speech perception •
Auditory system • •
Psycho-acoustics • •
Perception of speech units • •
Taxonomic phonemics •
Phonemes and allophones •
Minimal Pairs •
Syllable structure •
Phonological processes •
Distinctive features •
Jacobson: Acoustic features •
Generative Phonology: Sound pattern of English •
Rules •
Non-linear phonology •
Autosegmental phonology •
Metrical phonology •
Other non-linear models (e.g. feature geometry, dependency phonology) •

Cognitive Models for Speech and Language Processing top
LFM-2 CPL SR-1 SR-2 L+B
Introduction
The role of psychology in cognitive science •
The role of linguistics in cognitive science •
The contribution of computer science and AI •
The contribution of neuroscience •
Pattern recognition •
Learning and memory •
Knowledge representation •
Acoustic/phonetic perception
Cues, feature detectors •
Categorical perceptions •
Production-oriented theories: analysis by synthesis, motor theory, quantal theory • •
Perception-oriented theories: auditory theory of speech perception, hyper/hypo theory • •
Lexical recognition
Cohort models •
TRACE •
Neighbourhood models •
Lexical priming •
Frequency effects •
Language acquisition and language development •

Speech Signal Processing top
CPL SWL1 SigPro SR-1 SS1 SS2
Speech recording and digitisation • • •
Signal processing tools • •
Digital filters •
Fourier series and transforms (DFT, FFT) •
Short-term Fourier transforms •
Filter banks
Speech analysis and parameter extraction
Short-term analysis • • •
Time-domain analysis • •
Frequency-domain analysis • •
Cepstral analysis • •
Linear prediction analysis • •
Pitch and formant estimation • •
Speech signal synthesis • •
Speech coding
Speech enhancement

Pattern Recognition top
SWL1 SR-3 Stats SS1
Deterministic pattern recognition
Distances •
Data Clustering •
Decision and regression trees •
Dynamic programming and dynamic time warping •
Statistical pattern recognition
Maximum a posteriori and maximum likelihood classification •
Likelihood Estimation-Maximization (EM) algorithm •
Discriminant functions, artificial neural networks
Stochastic finite state automata and discrete Markov Models •
Hidden Markov Models (HMM) • •

Language Engineering Applications top
CPL SWL1 SWL2 SigPro SR-3 AlSyn L+B Stats SS1 SS2 Alg+Datastr. Cp Comptl. Lxgr. MT SLDS IR
Generic Technologies
Speech recognition • •
Speech synthesis / TTS • • •
Speaker identification / verification •
Text processing • • •
Text analysis / generation •
Integration of text and speech processing •
Multimodal integration •
Corpora • • • •
Current applications
Command-and-Control •
Intelligent MultiMedia (MultiModal) systems •
Spoken dialogue systems •
Information Retrieval (IR) and Extraction (IE) •
Dictation •
Machine Translation (MT) •
Computer Aided Language Learning (CALL)
Systems design
Requirements, development, evaluation and testing • •
Empirical methods (databases, knowledge elicitation e.g. Wizard of Oz) •
Architectures & communications systems
Standards e.g. EAGLES • •
Tools and platforms (hands-on experience)
Tools e.g. Waves, Matlab, Entropic, HTK • • • • •

Programming Languages top
CPL SigPro Pragm Plang1 Plang2
(one declarative language, examples for Prolog and Lisp)
Prolog • •
Lisp
(one procedural or script language, examples for C, java, Perl and Matlab) • • •
C • •
Java • • •
Perl •
Matlab