Incorporating Knowledge Sources Into Statistical Speech Recognition

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.

Incorporating Knowledge Sources Into Statistical Speech Recognition features in the following genres: Electronics engineering, Wave mechanics (vibration and acoustics), Electrical engineering, Communications engineering / telecommunications, Network hardware, Digital signal processing (DSP)

Incorporating Knowledge Sources Into Statistical Speech Recognition is available in Hardback

Incorporating Knowledge Sources Into Statistical Speech Recognition was written by Sakriani Sakti and published by Springer an imprint of Springer US

Incorporating Knowledge Sources Into Statistical Speech Recognition has 194 pages

Yes it is part of Lecture Notes in Electrical Engineering series