Inlämning av Examensarbete / Submission of Thesis

Mikael Nilsson; Marcus Ejnarsson MEE-01-27, pp. 98. Inst för telekommunikation och signalbehandling/Dept. of Telecommunications and Signal Processing, 2002.

The work

Författare / Author: Mikael Nilsson, Marcus Ejnarsson
Titel / Title: Speech Recognition using Hidden Markov Model
Abstrakt Abstract:

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.

Ämnesord / Subject: Signalbehandling - Signal Processing
Elektroteknik - Electrotechnology
Nyckelord / Keywords: HMM, MFCC, LPC, MEL, NN, Viterbi, Itakura, SNR, CEPSTRUM, Speech recognition

Publication info

Dokument id / Document id:
Program:/ Programme Elektroteknik
Registreringsdatum / Date of registration: 09/16/2004
Uppsatstyp / Type of thesis: D-Uppsats/Magister/Master


Handledare / Supervisor: Mattias Dahl
Examinator / Examiner: Mattias Dahl
Organisation / Organisation: Blekinge Institute of Technology
Institution / School: Inst för telekommunikation och signalbehandling/Dept. of Telecommunications and Signal Processing
Inst för telekommunikation och signalbehandling S-372 25 Ronneby
+46 455 38 50 00

Files & Access

Bifogad uppsats fil(er) / Files attached: speech recognition using hidden markov model.pdf (1541 kB, öppnas i nytt fönster)