- 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
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
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.
- 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