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A Symmetric Kernel Partial Least Squares Framework for Speaker Recognition
2013
IEEE Transactions on Audio, Speech, and Language Processing
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In this paper, we propose a kernel partial least squares (kernel PLS, or KPLS) framework for modeling speakers in the i-vectors space. ...
Recent advances in speaker recognition have utilized their ability to capture speaker and channel variability to develop efficient recognition engines. ...
Figure 2 : 2 (color) Kernel Partial Least Squares (KPLS) schematic for speaker recognition. ...
doi:10.1109/tasl.2013.2253096
fatcat:usebv7u2i5aflm2b6mi5325uma
MKPLS: Manifold Kernel Partial Least Squares for Lipreading and Speaker Identification
2013
2013 IEEE Conference on Computer Vision and Pattern Recognition
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We then factorize the parameter space using Kernel Partial Least Squares (KPLS) to achieve a low-dimension manifold latent space. ...
Our approach outperforms for the speaker semi-dependent setting by at least 15% of the baseline, and competes in the other two settings. ...
We propose to use kernel partial least square (KPLS) on the mapping coefficient space to achieve a supervised low-dimensional latent space for manifold parameterization. ...
doi:10.1109/cvpr.2013.94
dblp:conf/cvpr/BakryE13
fatcat:ecbp5gt52jbdxcaus5qxjahreu
A partial least squares framework for speaker recognition
2011
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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We develop a method for modeling the variability associated with each class (speaker) by using partial-least-squares -a latent variable modeling technique, which isolates the most informative subspace ...
for each speaker. ...
Motivated by this, we explore here a partial least squares based framework for speaker modeling and recognition in the supervector space. ...
doi:10.1109/icassp.2011.5947548
dblp:conf/icassp/SrinivasanZD11
fatcat:dodfty7wjfhv7b4kspkpwkwl4e
Intelligibility detection of pathological speech using asymmetric sparse kernel partial least squares classifier
2014
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Index Terms-Pathological speech, intelligibility of speech, kernel function, sparse kernel partial least squares regression, asymmetric sparse kernel partial least squares classifier ...
This paper proposes to use asymmetric sparse kernel partial least squares classifier (ASKPLSC) for intelligibility detection of pathological speech. ...
Therefore, we propose a sparse kernel partial least squares regression in the following for a normalized kernel matrix K. ...
doi:10.1109/icassp.2014.6854301
dblp:conf/icassp/HuangDL14
fatcat:55omhytvmbc47ns5jkq5ox2ivq
The UMD-JHU 2011 speaker recognition system
2012
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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of reverberation and noise via the use of frequency domain perceptual linear predictor and cortical features; 3) A new discriminative kernel partial least squares (KPLS) framework that complements state-of-the-art ...
In recent years, there have been significant advances in the field of speaker recognition that has resulted in very robust recognition systems. ...
Kernel partial least squares: Partial least squares (PLS) is a subspace based learning technique that has been used for dimensionality reduction as well as a regression and is popular due to its ability ...
doi:10.1109/icassp.2012.6288852
dblp:conf/icassp/Garcia-RomeroZZSLGTNSMMJRMEHSD12
fatcat:aobi62ffgjclpigqiiyfknaq5q
Manifold-Kernels Comparison in MKPLS for Visual Speech Recognition
[article]
2016
arXiv
pre-print
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We apply manifold kernel partial least squares framework to OuluVs and AvLetters databases, and show empirical comparison between all kernels. ...
This work is intended to evaluate the performance of several manifold kernels for solving the problem of visual speech recognition. We show the theory behind each kernel. ...
Each frame exposes only the mouth area of the speaker.
Framework description Manifold Kernel Partial Least Squares (MKPLS) framework is proposed in [13] . ...
arXiv:1601.05861v1
fatcat:5sftjcgxhrezza7vu6se3szlqa
Large-Scale Approximate Kernel Canonical Correlation Analysis
[article]
2016
arXiv
pre-print
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time prohibitive for large-scale problems. ...
Various approximation techniques have been developed for KCCA. ...
We thank Bo Xie for providing his implementation of the doubly stochastic gradient algorithm for approximate KCCA, and Nati Srebro for helpful discussions. ...
arXiv:1511.04773v4
fatcat:qdpld3we4nap7itnyj2rnwa5hy
LSTM Based Cross-corpus and Cross-task Acoustic Emotion Recognition
2018
Interspeech 2018
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Results indicate the suitability of the proposed method for both time-continuous and utterance level cross-corpus acoustic emotion recognition tasks. ...
In this work, we first investigate the suitability of Long-Short-Term-Memory (LSTM) models trained with time-and space-continuously annotated affective primitives for cross-corpus acoustic emotion recognition ...
In line with our recent experience on paralinguistic and multi-modal affective computing [10] , we employ least squares based classifiers such as Kernel Extreme Learning Machines (KELM) and Partial Least ...
doi:10.21437/interspeech.2018-2298
dblp:conf/interspeech/KayaFYVZ018
fatcat:ofp3attxybce5ilrgfnognhgym
A novel speech emotion recognition algorithm based on wavelet kernel sparse classifier in stacked deep auto-encoder model
2019
Personal and Ubiquitous Computing
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Therefore, in order to address the abovementioned issues, a novel speech emotion recognition algorithm based on improved stacked kernel sparse deep model is proposed in this paper, which is based on auto-encoder ...
Finally, a wavelet-kernel sparse SVM classifier is applied to classify the features. ...
And our proposed recognition rate for wavelet kernel least squares support vector (WKLLSVM) machine has reached 73.19%, fully demonstrating the superiority of our proposed classifier. ...
doi:10.1007/s00779-019-01246-9
fatcat:nv6kc6maffdtnhjo2qvgtvp7oi
Sub-Microwatt Analog VLSI Trainable Pattern Classifier
2007
IEEE Journal of Solid-State Circuits
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A 24-class, 14-input, 720-template classifier trained for speaker identification and fabricated on a 3 mm 3 mm chip in 0.5 m CMOS delivers real-time recognition accuracy on par with floating-point emulation ...
Subtractive normalization of the outputs by current-mode feedback produces confidence scores which are integrated for category selection. ...
The method facilitates increased programming speed while achieving a precision of at least 7 bits, which in most cases is sufficient for recognition tasks. Fig. 11 Fig. 11. ...
doi:10.1109/jssc.2007.894803
fatcat:kwoig46jbvfbdg5zeokfvjjy6a
Whispered Speech Recognition using Hidden Markov Models and Support Vector Machines
2018
Acta Polytechnica Hungarica
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The experiments are conducted in both Speaker Dependent (SD) and Speaker Independent (SI) fashion for Whi-Spe speech database. ...
At the same time, HMMbased recognition gave the highest recognition accuracy in SI fashion (87.42%). The results in recognition of neutral speech are given as well. ...
TR32032, and TR32035, EUREKA project DANSPLAT, "A Platform for the Applications of Speech Technologies on Smartphones for the Languages of the Danube Region", id Е! ...
doi:10.12700/aph.15.5.2018.5.2
fatcat:6w2cplw4ijhtland2zspipaeve
Fusing Acoustic Feature Representations for Computational Paralinguistics Tasks
2016
Interspeech 2016
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After nonlinear preprocessing, obtained Fisher vectors are kernelized and mapped to target variables by classifiers based on Kernel Extreme Learning Machines and Partial Least Squares regression. ...
The INTERSPEECH ComParE challenge series has a field-leading role, introducing novel problems with a common benchmark protocol for comparability. ...
This research is financially supported by the Russian Foundation for Basic Research (project № 16-37-60100). ...
doi:10.21437/interspeech.2016-995
dblp:conf/interspeech/KayaK16
fatcat:pt5a3oltxrhftefrjy7uuhzese
Computational Intelligence-Based Biometric Technologies
2007
IEEE Computational Intelligence Magazine
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CI-based methods, including neural network and fuzzy technologies, have also been extensively investigated for biometric matching. ...
CI-based biometric technologies are powerful when used in the representation and recognition of incomplete biometric data, discriminative feature extraction, biometric matching, and online template updating ...
Acknowledgments The work is partially supported by the UGC/CRC fund from the HKSAR Government, the central fund from the Hong Kong Polytechnic University and the National Natural Science Foundation of ...
doi:10.1109/mci.2007.353418
fatcat:aynahy3ttbesfl3qm3u25gcawq
Svm-Based Lost Packets Concealment For Asr Applications Over Ip
2002
Zenodo
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employed dynamic parameters (delta) produces at least one or two frames delay. ...
Estimation experiments To gain some insight on the problem, we have compared the mean-square error (MSE) for both the repetition procedure and the SVM regressor and the results, highly favourable to the ...
doi:10.5281/zenodo.53611
fatcat:hx7hyxqu5bd6xfvqcyuzl7chuq
Visual Speech Recognition and Utterance Segmentation Based on Mouth Movement
2007
9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007)
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Segmentation of utterances is important in a visual speech recognition system. ...
., human computer interface (HCI) for mobility-impaired users, lip-reading mobile phones, in-vehicle systems, and improvement of speech-based computer control in noisy environments. ...
The speed of phonation of the speaker might vary for each repetition of the same phone. ...
doi:10.1109/dicta.2007.4426769
dblp:conf/dicta/YauWK07
fatcat:vdoxdzikl5b5zmnmqe32dowizq
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