Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Technical Assistance for Motor- and Multiple Disabled Children - Some Long Term Experiences
ICCHP '02 Proceedings of the 8th International Conference on Computers Helping People with Special Needs
Technical assistance for severely motor- and multiple impaired children
CBMS '97 Proceedings of the 10th IEEE Symposium on Computer-Based Medical Systems (CBMS '97)
Disordered speech assessment using automatic methods based on quantitative measures
EURASIP Journal on Applied Signal Processing
Modeling state durations in hidden Markov models for automatic speech recognition
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Hidden control neural architecture modeling of nonlinear time varying systems and its applications
IEEE Transactions on Neural Networks
Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition
IEEE Transactions on Audio, Speech, and Language Processing
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The Viterbi dynamic programming algorithm is currently the de-facto standard for speech recognizers to deal with duration variations of the sub-word units of speech by properly aligning the sub-word units to the sub-word unit models. The algorithm is an integral part of the hidden Markov model speech recognizers. In this work a robust and simple voice command system is developed, implemented and tested. It uses a novel speech alignment algorithm, the so-called "run-length limited dynamic programming algorithm" (RLL-DP) instead. The voice command system described hereinafter facilitates the operation of the AUTONOMY system, which is an environmental control system combined with an alternative and augmentative communication system, using isolated words as voice commands. The activation of "run-length limits" causes a statistically significant reduction of the word error rate, even when using simple "centroid sequence word models" instead of acoustic models based on "hidden control neural networks" used in previous versions.