Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/49638
Title: Extreme learning machine based speaker verification
Authors: Xu, Cheng.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Issue Date: 2012
Abstract: Speaker recognition is a technique of automatically recognizing who is speaking by using the speaker-specific information. Speaker verification is one of the speaker recognition aspects. It is the process of accepting or rejecting the identity claimed by a speaker. Extreme Learning Machine (ELM) is one of the computational intelligence techniques. It was proposed by Prof. Huang Guangbin, School of Electrical & Electronic Engineering, Nanyang Technological University. The past research has shown that ELM is superior to other techniques in the speech processing aspect. So it is worth to apply ELM to the speaker verification system that will make the system more efficient and reliable. The aim of this project is to develop a text-independent speaker verification system base on ELM. This report will show how the author achieves this goal. It includes the basic principle for speaker verification system, selection of speech corpus, feature extraction technique, speaker modeling technique and programming process etc. The author also provides detailed process of the project implementation, and some discussion on certain issues found in the project. At last, the author will provide recommendations for future work about this project.
URI: http://hdl.handle.net/10356/49638
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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