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The effect of orthokeratology lens optical zone size on myopia control in adolescents. [PDF]
Lai L +6 more
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Direct all-electrical decoding of vector vortex beams on chip. [PDF]
Dai M +5 more
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An i-vector backend for speaker verification
Interspeech 2015, 2015We propose a new approach to the problem of uncertainty modeling in text-dependent speaker verification where speaker factors are used as the feature representation. The state-of-the-art backend in this situation consists in using point estimates of speaker factors to model the joint distribution of pairs of enrollment and test feature vectors under ...
Patrick Kenny +3 more
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Efficient approximated i-vector extraction
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012I-vectors are currently widely used by state-of-the-art speech processing systems for tasks such as speaker verification and language identification. A shortcoming of i-vector-based systems is that the i-vector extraction process is computationally expensive. In this paper we propose an efficient method to extract i-vectors approximately.
Hagai Aronowitz, Oren Barkan
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Simplification and optimization of i-vector extraction
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011This paper introduces some simplifications to the i-vector speaker recognition systems. I-vector extraction as well as training of the i-vector extractor can be an expensive task both in terms of memory and speed. Under certain assumptions, the formulas for i-vector extraction—also used in i-vector extractor training—can be simplified and lead to a ...
Ondrej Glembek +4 more
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e-vectors: JFA and i-vectors revisited
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017Systems based on i-vectors represent the current state-of-the-art in text-independent speaker recognition. In this work we introduce a new compact representation of a speech segment, similar to the speaker factors of Joint Factor Analysis (JFA) and to i-vectors, that we call “e-vector”.
CUMANI, SANDRO, LAFACE, Pietro
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Quasi-Factorial Prior for i-vector Extraction
IEEE Signal Processing Letters, 2015We analyze the i-vector extraction from the perspective of the prior distribution exerted on the mean supervector of Gaussian mixture model (GMM). To this end, we start off with the analysis of the subspace prior which leads to the compressed representation in the standard i-vector extraction.
Liping Chen +3 more
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Senone I-vectors for robust speaker verification
2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2016Recent research has shown that using senone posteriors for i-vector extraction can achieve outstanding performance. In this paper, we extend this idea to robust speaker verification by constructing a deep neural network (DNN) comprising a deep belief network (DBN) stacked on top of a denoising autoencoder (DAE).
Zhili Tan +3 more
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An Investigation on the Use of i-Vectors for Robust ASR
Interspeech 2016, 2016In this paper we propose two different i-vector representations that improve the noise robustness of automatic speech recognition (ASR). The first kind of i-vectors is derived from ``noise only'' components of speech provided by an adaptive denoising algorithm, the second variant is extracted from mel filterbank energies containing both speech and ...
Dimitrios Dimitriadis +2 more
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