Speech Processing (P01423)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : PPL-P-SP-LING

Syllabus: Fundamentals of speech processing (familiarity with waveforms, spectra, spectrograms, resonance, formants, human speech production and perception, perceptually-motivated frequency scales, time vs. frequency representations; conversion between the two, the Fourier transform, source-filter model of speech, hands on experience via xwaves), speech recognition (components of a typical recogniser, parameterisation of the speech signal, dynamic time warping, distance measures, the Hidden Markov Model, the generative model paradigm, simple probability theory, conditional and joint probabilities, Bayes' theorem, Gaussian probability density function, continuous density HMMs, monophone models with Gaussian observation densities, Viterbi algorithm for recognition, training from fully labelled data, Viterbi training, bigram language models), speech synthesis (components of a typical text-to-speech synthesiser, text analysis, phonology, finite-state automata, POS tagging, lexicon, phrasing, accents, F0, learning from data, CART models, waveform generation, concatenative methods - TD-PSOLA and linear prediction, F0 and duration modification).

Shared with UG Course U03221 Speech Processing (Hons).

Venue:
Tuesday - B9, Adam Ferguson Building
Thursday - B12, Adam Ferguson Building (TBC)

Entry Requirements

? Costs : None

Subject Areas

Home subject area

Language Sciences, (School of Philosophy, Psychology and Language Sciences, Schedule I)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 1 (Blocks 1-2)

? Contact Teaching Time : 2 hour(s) per week for 11 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
18/09/2007	09:00	11:00			B9, Adam Ferguson Building

All of the following classes

Type	Day	Start	End	Area
Lecture	Tuesday	09:00	10:50	Central

Summary of Intended Learning Outcomes

After taking this module, students should be able to:
- give an overview of the components of state-of-the art speech recognition and speech synthesis systems;
- understand the main concepts and what each component does;
- describe a simple version of each component;
- see what the difficult problems are in recognition and synthesis. They will also: use tools for visualising and manipulating speech waveforms;
- experiment with two state-of-the-art speech technology systems;
- put experimental methodology into practice;
- see how knowledge and skills from different areas come together in an interdisciplinary field.