Robust text-independent speaker identification using Gaussian ...
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Douglas A. Reynolds, Member, IEEE, and Richard C. Rose, Member, IEEE.
Abstract— This ... D. A. Reynolds is with the Speech Systems Technology Group,
MIT.
(GMM) for robust text-independent speaker identification. The individual Gaussian ..... step was denoising dataset using wave atom transformation then applying ...
TIMIT database and on a subset of the NTIMIT database are pre- sented. The new algorithm is shown to offer improved recognition rates over other existing ...
Jul 8, 2016 - PLOS ONE | DOI:10.1371/journal.pone.0158520 July 8, 2016. 1 / 21 a11111 .... dependent rate and phase responses, shift in the best frequency with level, adaptation, and sev- eral high-level .... Illustration of the effects of noise on t
The text-independent, closed-set speaker identification accuracies, as tested on KING, YOHO and the down-sampled version of. TIMIT databases were 98.81%, ...
text-independent speaker identification from samples of speech recorded over the ...... neering from McMaster University, Hamilton, Ont.,. Canada, in 1986, and ...
The performance is evaluated using clean speech corpus from TIMIT database combined with babble noise from the NOISEX-92 database. Experimental.
Douglas A. Reynolds, Thomas F. Quatieri, and Robert B. Dunn .... Reynolds,
Quatieri, and Dunn: Speaker Verification Using Adapted GMMs. 21. FIG. 1.
independent speaker identification on very short utterances. The tech- nique is based on ... effective parametric classifier for speaker identification in a telephone.
Broadcast news : Radio and TV programs with vari- ous kinds of programming, ..... [1] S. Chen and P. Gopalakrishnan, âSpeaker, environ- ment and channel ...
For acoustic speaker localization, we use a number of spatially distributed microphone sensors to capture in- coming sound waves. If the amplitude gradient ...
Robust Speaker Recognition using Microphone Arrays. Iain A. McCowan. Jason Pelecanos. Sridha Sridharan. Speech Research Laboratory, RCSAVT, School ...
Sep 2, 2011 - the Mel-Frequency Cepstral Coefficients (MFCC) and their first and second ..... [6] S. Davis and P. Mermelstein, âComparison of paramet-.
monitoring location where an operator is responsible for dozens of monitors to visually .... final image below is used to calculate the location of the moving target.
signal energy conserving, PSD is used to concentrate the signal energy and the .... [13] Wavelet tutorial by R.B.Polikar,volume III AND VOL.IV,on computers,.
speaker identification model is developed by integrating. MFCC's with Independent .... New dataset =Wica* Mean Adjusted original Data, where, Wica is the ...
approach, in which client and test speaker models are confined to a low-dimensional linear ... 100 client speakers for a
familiar resonances below 4000 Hz, and a third setup is designed to approximate the .... are commonly used as a front-end for both speech recognition.
is known as the variance function in the GLIM theory, respectively. 2.2 Expectation-Maximization (EM) Algorithm. The EM algorithm is a general technique for ...
1929; e-mail: [email protected]). extraction of speaker dependent features from the speech signal is the fundamental problem of speaker recognition.
quality i-vector to construct a discriminative dictionary in SRC, supporting effective speaker identification. Besides improving dictionary from the i-vector aspect, ...
vowels and voiced consonants are relatively more effective for accurate speaker identification [5-6]. In our previous experiments, we conducted perceptual.
Air Force Research Laboratory/IFEC,. 32 Brooks Rd. Rome NY 13441-4514 .... Fifth, the standard error for the percent cor
Robust text-independent speaker identification using Gaussian ...
Dr. Joseph Campbell. D. A. Reynolds is with the Speech Systems Technology Group, MIT ..... Institute of Technology Lincoln Laboratory, where his research ...
