Incorporating Knowledge Sources into Statistical Speech Recognition

Description

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.

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1. Ebooks list page : 2613
2. Incorporating Knowledge Sources into Statistical Speech Recognition (Lecture Notes in Electrical Engineering)
3. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
4. Speech Recognition
5. Distant Speech Recognition
6. Speech Synthesis and Recognition
7. Fundamentals of Speech Recognition
8. Speech & Audio Processing and Recognition
9. Digital Speech Processing, Synthesis and Recognition
10. Pattern Recognition in Speech and Language Processing
11. Visual Speech Recognition: Lip Segmentation and Mapping
12. Pattern Recognition in Speech and Language Processing
13. Pattern Recognition in Speech and Language Processing
14. [share_ebook] Speech Recognition using Neural Networks
15. Speech Recognition Over Digital Channels: Robustness and Standards
16. Robust Speech Recognition in Embedded Systems and PC Applications