Sequence recognition is a crucial element in many applications in the fields of speech analysis and recognition, time-series prediction, control and signal monitoring. This book applies the techniques of neural networks and hidden Markov models to problems of pattern and speech recognition, using real-world examples throughout.

Highlights include the incorporation of domain knowledge with learning from examples, the description of contemporary advances such as recurrent neural networks, hybrids with hidden Markov models, and a thorough but straightforward use of mathematics. Neural Networks for Speech and Sequence Recognition will prove valuable to researchers and graduate students alike.