scholarly journals Robust Digital Speech Watermarking For Online Speaker Recognition

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
Hamurabi Gamboa-Rosales ◽  
Mohammad Ali Akhaee ◽  
S. A. R. Al-Haddad
Keyword(s):  
Speaker Recognition ◽  
Speaker Verification ◽  
Discrete Wavelet ◽  
Specific Information ◽  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Discrete Wavelet Packet Transform ◽  
Speech Watermarking ◽  
Digital Speech Watermarking ◽  
Institute Of Technology

A robust and blind digital speech watermarking technique has been proposed for online speaker recognition systems based on Discrete Wavelet Packet Transform (DWPT) and multiplication to embed the watermark in the amplitudes of the wavelet’s subbands. In order to minimize the degradation effect of the watermark, these subbands are selected where less speaker-specific information was available (500 Hz–3500 Hz and 6000 Hz–7000 Hz). Experimental results on Texas Instruments Massachusetts Institute of Technology (TIMIT), Massachusetts Institute of Technology (MIT), and Mobile Biometry (MOBIO) show that the degradation for speaker verification and identification is 1.16% and 2.52%, respectively. Furthermore, the proposed watermark technique can provide enough robustness against different signal processing attacks.

scholarly journals Optimised Features for Speaker Identification using Daubechies Wavelet based Variance Spectral Flux

2021 ◽  
Author(s):  
Chander Prabha ◽  
Sukhvinder Kaur ◽  
Meenu Gupta ◽  
Fadi Al-Turjman
Keyword(s):  
Speaker Recognition ◽  
Speech Signal ◽  
Speaker Identification ◽  
Speaker Verification ◽  
Information Criteria ◽  
Identification System ◽  
Discrete Wavelet ◽  
Specific Information ◽  
Spectral Flux ◽  
Approximation Coefficients

Abstract An important application of speech processing is speaker recognition, which automatically recognizes the person speaking in an audio recording, basis of which is speaker-specific information included in its speech features. It involves speaker verification and speaker identification. This paper presents an efficient method based on discrete wavelet transform and optimized variance spectral flux to enhance the enactment of speaker identification system. An effective feature extraction technique uses Daubechies 40 (db40) wavelet to compress and de-noised the speech signal by its decomposition into approximations and details coefficients at level 1. The approximation coefficients contain 99.9% of speech information as compared to detailed coefficients. So, the optimized variance spectral flux is applied on wavelet approximation coefficients which efficiently extract the frequency contents of the speech signal and gives unique features. The distance between extracted features has been obtained by applying traditional Bayesian information criteria. Experimental results were computed on recording data of 33 speakers (23 female and 10 males) for text independent identification of speaker. Evaluation of effectiveness of the proposed system is done by applying detection error trade-off curves, receiver operating characteristic, and area under curve. It shows 94.38% of speaker identification results when compared with traditional method using Mel frequency spectral coefficients which is 90.70%.

XX Rudi Dombusch, Keys to Prosperity. Free Markets, Sound Money, and bit of Luck The MIT Press 2000 Londres

2009 ◽  
Vol 33 (130) ◽  
Author(s):  
GERARDO REYES GUZMÁN
Keyword(s):  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Free Markets ◽  
Institute Of Technology

Rudiger Dornbusch, destacado economista del Massachusetts Institute of Technology (MIT), analiza en esta trascendental obra tópicos como inflación, deuda, tipos de cambio, política externa y mercados emergentes. El marco conceptual descansa en la corriente de la escuela de Chicago, la cual parte del principio de que el mercado es el mecanismo que garantiza la creación del progreso en contraste con el Estado, que en su afán por encontrar soluciones perfectas, fracasa regularmente en sus cometidos.

Life sciences intellectual property licensing at the Massachusetts Institute of Technology

2021 ◽  
Vol 39 (3) ◽  
pp. 293-301
Author(s):  
Samuel Huang ◽  
Kien Wei Siah ◽  
Detelina Vasileva ◽  
Shirley Chen ◽  
Lita Nelsen ◽  
...  
Keyword(s):  
Intellectual Property ◽  
Life Sciences ◽  
Massachusetts Institute ◽  
Massachusetts Institute Of Technology ◽  
Institute Of Technology
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