Mikael Nilsson; Marcus Ejnarsson MEE-01-27, pp. 98. Inst för telekommunikation och signalbehandling/Dept. of Telecommunications and Signal Processing, 2002.
The purpose with this final master degree project was to develop a speech recognition tool, to make the technology accessible. The development includes an extensive study of hidden Markov model, which is currently the state of the art in the field of speech recognition. A speech recognizer is a complex machine developed with the purpose to understand human speech. In real life this speech recognition technology might be used to get a gain in
traffic security or facilitate for people with functional
disability. The technology can also be applied to many other areas. However in a real environment there exist disturbances that might influence the performance of the speech recognizer. The report includes an performance evaluation in different noise situations, in a car environment. The result shows that the recognition rate varies from 100%, in a noise free environment,
to 75% in a more noisy environment.