Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.
Publisher: Springer-Verlag New York Inc.
Number of pages: 196
Weight: 343 g
Dimensions: 235 x 155 x 11 mm
Edition: Softcover reprint of hardcover 1st ed. 2009