Speech Recognition using Hidden Markov Model
Independent thesis Advanced level (degree of Master (One Year))Student thesis
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.
Place, publisher, year, edition, pages
2002. , 98 p.
HMM, MFCC, LPC, MEL, NN, Viterbi, Itakura, SNR, CEPSTRUM, Speech recognition
Signal Processing Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:bth-3946Local ID: oai:bth.se:arkivexE156A6197D8B0678C1256BBB003F6207OAI: oai:DiVA.org:bth-3946DiVA: diva2:831263