Programming for Language Technology II

Python and NLTK, Access to text corpora and lexical resources (e.g. Wordnet), Processing of raw text, Develop structured programs, Text/Word annotation (e.g.POS tagging), Text classification, Information extraction from text, Extract sentence structure , Grammatical analysis. Language models, word embeddings, n-grams, evaluation with precision, recall, F-measure and accuracy.

Data processing, Python , entry / exit audio files (wav, mp3, ogg, flac, etc.), Signal processing blocks (FFT, DCT, frame cutter, windowing, envelope, smoothing), Filters FIR & IIR (low / high / band pass, band reject, DC removal, equal loudness), statistics (median, mean, standard deviation, power means, raw and central moments, spread, kurtosis, skewness, flatness), Time-domain descriptors (duration, loudness, zero-crossing-rate, log attack time and other signal envelope descriptors) Spectral descriptors (Bark / Mel / ERB bands, MFCC, GFCC, LPC, spectral peaks).

INSTRUCTOR

galanisdatathenarc [dot] gr (Dimitrios Galanis)
maximosatathenarc [dot] gr (Maximos Kaliakatsos -
Papakostas)

COURSE DESCRIPTION:
COURSE CODE
C28
SEMESTER
Spring
COURSE TYPE
Postgraduate (PG)
ECTS
6