2017 Regulation IT8077 Speech Processing Syllabus

OBJECTIVES:

• To understand the fundamentals of the speech processing
• Explore the various speech models
• Gather knowledge about the phonetics and pronunciation processing
• Perform wavelet analysis of speech
• To understand the concepts of speech recognition

UNIT I INTRODUCTION 9

Introduction – knowledge in speech and language processing – ambiguity – models and algorithms – language – thought – understanding – regular expression and automata – words & transducers –N grams

UNIT II SPEECH MODELLING 9

Word classes and part of speech tagging – hidden markov model – computing likelihood: the forward algorithm – training hidden markov model – maximum entropy model – transformationbased tagging – evaluation and error analysis – issues in part of speech tagging – noisy channel model for spelling

UNIT III SPEECH PRONUNCIATION AND SIGNAL PROCESSING 9

Phonetics – speech sounds and phonetic transcription – articulatory phonetics – phonological categories and pronunciation variation – acoustic phonetics and signals – phonetic resources -articulatory and gestural phonology

UNIT IV SPEECH IDENTIFICATION 9

Speech synthesis – text normalization – phonetic analysis – prosodic analysis – diphone waveform synthesis – unit selection waveform synthesis – evaluation

UNIT V SPEECH RECOGNITION 9

Automatic speech recognition – architecture – applying hidden markov model – feature extraction:mfcc vectors – computing acoustic likelihoods – search and decoding – embedded training -multipass decoding: n-best lists and lattices- a* (‗stack‘) decoding – context-dependent acoustic models: triphones – discriminative training – speech recognition by humans

TOTAL : 45 PERIODS

OUTCOMES:

On Successful completion of the course ,Students will be able to

•  Create new algorithms with speech processing
•  Derive new speech models
•  Perform various language phonetic analysis
•  Create a new speech identification system
•  Generate a new speech recognition system

TEXT BOOK:

1. Daniel Jurafsky and James H. Martin, ― Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition‖, Person education,2013.

REFERENCES

• 1. Kai-Fu Lee, ―Automatic Speech Recognition‖, The Springer International Series in Engineering and Computer Science, 1999.
• 2. Himanshu Chaurasiya, ―Soft Computing Implementation of Automatic Speech Recognition‖,LAP Lambert Academic Publishing, 2010.
• 3. Claudio Becchetti, Klucio Prina Ricotti, ―Speech Recognition: Theory and C++ implementation‖,Wiley publications 2008.
• 4. Ikrami Eldirawy , Wesam Ashour, ―Visual Speech Recognition‖, Wiley publications , 2011

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