Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/41749
Title: Psychoacoustic model for robust speech recognition
Authors: Luo, Xue Wen
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2008
Source: Luo, X. W. (2008). Psychoacoustic model for robust speech recognition. Master’s thesis, Nanyang Technological University, Singapore.
Abstract: This thesis presents a detailed study on psychoacoustic modeling for feature extraction for robust speech recognition. In an automatic speech recognition (ASR) system, feature extraction is critical to determining the recognizer's performance. The most popular feature vectors for ASR are Mel Frequency Cepstral Coefficients (MFCC). However, it is also well known that its performance drops dramatically under noisy condition. One of the objectives of this thesis is to improve the robustness of a recognizer. Compared to an ASR system, human is good at tolerating background noise, hence psychoacoustic modeling of human hearing system is investigated and integrated into speech features extraction process of a speech recognizer to increase the robustness of it.
URI: https://hdl.handle.net/10356/41749
DOI: 10.32657/10356/41749
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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