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Author: | Keraudy, Stevan |
Title: | Histogram equalization for noise robust speech recognition |
Publication type: | Master's thesis |
Publication year: | 2009 |
Pages: | (5+) 50 Language: eng |
Department/School: | Tietotekniikan laitos |
Degree programme: | Tietotekniikan tutkinto-ohjelma |
Main subject: | Informaatiotekniikka (T-61) |
Supervisor: | Oja, Erkki |
Instructor: | Kurimo, Mikko |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
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Location: | P1 Ark Aalto 7154 | Archive |
Keywords: | speech recognition histogram equalization noise robustness |
Abstract (eng): | Automatic speech recognition (ASR) is a fascinating field of science where the machine almost becomes human. Being able to communicate naturally with a machine has been a dream for a long time. Today, the technology makes it possible for the machine to understand human speech. However the quality of recognition suffers a lot from surrounding noise, and noisy environments are our everyday life conditions. This work presents a technique to improve noise robustness of ASR systems based on histogram equalization. This method has been proven efficient in the field of image processing and here we show that it can he successfully applied to audio data too. The idea behind it is to equalize noisy data and make it "sound like" clean data so that ASR systems trained on clean speech can recognize noisy speech more accurately. Experiments are conducted on Helsinki University of Technology's ASR system, and show a significant improvement in large vocabulary continuous speech recognition of noisy data on Aurora 4 database. |
ED: | 2009-10-05 |
INSSI record number: 38413
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