Type of Document Master's Thesis Author McMillan, David Evans URN etd-11172012-040049 Title Time-varying linear prediction as a base for an isolated-word recognition algorithm Degree Master of Science Department Electrical Engineering Advisory Committee
Advisor Name Title Beex, A. A. Louis Committee Chair Nunnally, Charles E. Committee Member Vanlandingham, Hugh F. Committee Member Keywords
- Numerical analysis
Date of Defense 1987-05-05 Availability restricted Abstract
There is a vast amount of research being done in the area of voice recognition. A large portion of this research concentrates on developing algorithms that will yield higher accuracy rates; such as algorithms based on dynamic time warping, vector quantization, and other mathematical methods [l2][l5].
In this research, the evaluation of the feasibility of using linear prediction (LP) with time-varying parameters as a base for a voice recognition algorithm will be investigated. First the development of an anti-aliasing filter is discussed with some results from the filter hardware realization included. Then a brief discussion of LP is presented and a method for time-varying LP is derived from this discussion. A comparison between time-varying and segmentation LP is made and a description of the developed algorithm that tests time-varying LP as a recognition technique is given. The evaluation is conducted with the developed algorithm configured for speaker-dependent and speaker-independent isolated-word recognition.
The conclusion drawn from this research is that this particular technique of voice recognition is very feasible as a base for a voice recognition algorithm. With the incorporation of other techniques, a complete algorithm can conceivably be developed that will yield very high accuracy rates. Recommendations for algorithm improvements are given along with other techniques that might be added to make a complete recognition algorithm.
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