After we decided to do final project on joint speech and speaker recognition, we did a lot of research and downloaded almost 2 GB of articles, lecture notes and etc. But, these article(around 30 MB) were really useful to us.
All of them are available on Web for free. Just google it.
- Assignment 3: GMM Based Speaker Identification EN2300 Speech Signal Processing, [ www.kth.se/polopoly_fs/1.41342!assignment_03.pdf]
- Conrad Sanderson, Automatic Person Verification Using Speech and Face Information - A Dissertation Presented to The School of Microelectronic Engineering Faculty of Engineering and Information Technology, Griffith University, August 2002, [revised February 2003].
- Douglas A Reynolds and Richard C Rose, Robust text-independent speaker identification using Gaussian mixture speaker models. IEEE Transactions on Speech and Audio Processing, 3(1):72–83, 1995.
- G. Saha, Sandipan Chakroborty, Suman Senapati , A New Silence Removal and Endpoint Detection Algorithm for Speech and Speaker Recognition Applications, Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Khragpur, Kharagpur, India.
- J P Campbell, Jr. Speaker recognition: A tutorial. Proc. IEEE, 85(9):1437–1462, 1997.
- K.R. Aida–Zade, C. Ardil and S.S. Rustamov, Investigation of Combined use of MFCC and LPC Features in Speech Recognition Systems, World Academy of Science, Engineering and Technology, 2006
- L. R. Rabiner, “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition”, vol-77, no. 2, pp. 257-286, 1989.
- Lasse L Mølgaard, Kasper W Jørgensen, Speaker Recognition: Special Course; IMM-DTU; 2005
- Mohamed Faouzi BenZeghibaa , Joint Speech and Speaker Recognition,IDIAP Research Report, 2005.
- Robin Teo Choon Guan @ Myo Thant, Majority Rule- Based Non-Intrusive User Authentication by Speech: Part 2 (Speaker Verification), Thesis, School of Science and Technology, Sim University,2009.
- Shi-Huang Chen and Yu-Ren Luo , Speaker Verification Using MFCC and Support Vector Machine, Proceedings of the International Multi Conference of Engineers and Computer Scientists 2009, vol – I, IMECS 2009.
- Tomi Kinnunen , Spectral Features for Automatic Text-Independent Speaker Recognition- Licentiate’s Thesis, University of Joensuu, Department of Computer Science, Finland, 2003.
- Waleed H. Abdulla and Nikola K. Kasabov, The Concepts of Hidden Markov Model in Speech Recognition, Knowledge Engineering Lab, Department of Information Science, University of Otago,New Zealand, 1999.
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ReplyDeletelife saver! thanks! :)
ReplyDeleteGanesh Can you help me to find the features of the sound that i have recorded.
ReplyDeleteI have done upto FFT and its imaginary part are set to zero.
I am stuck in the extraction of MFCC in C#.
I am from ACEM,kupondole,Nepal
We are doing final year project on speech recognition with HMM so will u be kind to help me
I have try to mail u but couldnot send to ur id below
Hi,
DeleteI am not sure where you got stuck. Is it on understanding the algorithm(s) or implementing it?
I assume you have already read my final year project report. You can find it from here : http://ganeshtiwaridotcomdotnp.blogspot.com/2011/06/final-report-text-prompted-remote.html
The block diagrams and descriptions of the MFCC feature extraction might be helpful to you.
If you need help on implementing the algorithm, you can find the codes (written in Java) from the googlecode link i gave in http://ganeshtiwaridotcomdotnp.blogspot.com/2012/05/speech-recognition-java-code-hmm-vq.html.
If you understand the codes in java, it wouldn't be difficult to you to write into C#.
Hope this helps.