Efficient Speaker Identification from Speech Transmitted on Bluetooth

Ali Khalil

ISBN 10: 3330851139 / ISBN 13: 9783330851139

Published by Noor Publishing Mär 2017, 2017

About this Item

Neuware -This book presents a study for speaker recognition rates for speech transmitted through Bluetooth channel as a degraded speech signals, while training phase is made by clean speech. This is based on the Mel-frequency cepstral coefficients (MFCC) for feature extraction from the speech. Different approaches for feature extractions was experimented; features from signal, feature from DCT, from signal plus DCT, features from DST, from signal plus DST, DWT of signal, and from signal plus DWT. The book introduces how Neural Network (NN) classification technique is used in the experiment as a classifier. In the training phase of experiments, the MFCCs and polynomial coefficients are estimated to form the feature vectors of the database. In the testing phase, similar features to that used in the training are extracted from the degraded or transmitted samples and used for matching. This book has investigated the process of speaker identification from speech transmitted over Bluetooth system. How the recognition rate for SNR above 0 dB is getting improved, and how the energy compaction property of the DCT allows robust features to be extracted from few samples.Books on Demand GmbH, Überseering 33, 22297 Hamburg 128 pp. Englisch.

Seller Inventory # 9783330851139

Bibliographic Details

• Title: Efficient Speaker Identification from Speech Transmitted on Bluetooth
• Publisher: Noor Publishing Mär 2017
• Publication Date: 2017
• Language: English
• ISBN 10: 3330851139
• ISBN 13: 9783330851139
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 9D millimeters 220 millimeters width by 150 millimeters height by 9 millimeters depth
• Weight: 209 grams

About this title

Synopsis

This book presents a study for speaker recognition rates for speech transmitted through Bluetooth channel as a degraded speech signals, while training phase is made by clean speech. This is based on the Mel-frequency cepstral coefficients (MFCC) for feature extraction from the speech. Different approaches for feature extractions was experimented; features from signal, feature from DCT, from signal plus DCT, features from DST, from signal plus DST, DWT of signal, and from signal plus DWT. The book introduces how Neural Network (NN) classification technique is used in the experiment as a classifier. In the training phase of experiments, the MFCCs and polynomial coefficients are estimated to form the feature vectors of the database. In the testing phase, similar features to that used in the training are extracted from the degraded or transmitted samples and used for matching. This book has investigated the process of speaker identification from speech transmitted over Bluetooth system. How the recognition rate for SNR above 0 dB is getting improved, and how the energy compaction property of the DCT allows robust features to be extracted from few samples.

About the Author

Ali Ahmed KhalilBorn in Egypt, 1981.Graduated in faculty of engineering, Tanta University in 2003.Has many publications in international magazines and conferences. Received his Msc degree in June 2014.He occupied many academic and executive positions as well.