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1
End-to-End Attention based Text-Dependent Speaker Verification ...
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2
A unified framework of HMM adaptation with joint compensation of additive and convolutive distortions
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 23 (2009) 3, 389-405
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3
A novel framework and training algorithm for variable-parameter hidden Markov models
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 17 (2009) 7, 1348-1360
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4
Robust speech recognition using a cepstral minimum-mean-square-error-motivated noise suppressor
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 16 (2008) 5, 1061-1070
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5
A study of variable-parameter Gaussian mixture hidden Markov modeling for noisy speech recognition
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 15 (2007) 4, 1366-1376
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6
A method of joint compensation of additive and convolutive distortions for speaker-independent speech recognition
In: Institute of Electrical and Electronics Engineers. IEEE transactions on speech and audio processing. - New York, NY : Inst. 13 (2005) 5, 975-983
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7
Estimation of mixtures of stochastic dynamic trajectories : application to continuous speech recognition
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 10 (1996) 1, 23-36
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8
Comparative experiments of several adaptation approaches to noisy speech recognition using stochastic trajectory models
In: Speech communication. - Amsterdam [u.a.] : Elsevier 18 (1996) 4, 335-352
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9
Speech recognition in noisy environments : a survey
In: Speech communication. - Amsterdam [u.a.] : Elsevier 16 (1995) 3, 261-291
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10
Off-Line Handwriting Recognition by Statistical Correlation
In: IAPR Workshop on Machine Vision Applications - MVA'94 ; https://hal.inria.fr/inria-00533959 ; IAPR Workshop on Machine Vision Applications - MVA'94, IAPR, Dec 1994, Kawasaki, Japan. pp.371-374 ; http://b2.cvl.iis.u-tokyo.ac.jp/mva/proceedings/CommemorativeDVD/1994/papers/1994371.pdf (1994)
Abstract: International audience ; In this paper, we present a new approach to unconstrained, off-line handwriting recognition (HWR). It is based on the global plausibility estimation of a word knowing the local probability of each individual character. Having a set of character models issued from a training step and an input word pattern, we maximize for each word of the lexicon the sum of plausibilities of its component characters. This maximisation is made in terms of observation quality and extent of a symbol within the pattern. The proposrd method operates in a top-down manner by giving srgmentation hypotheses which induce local symbol rxtcnts for a given word of the lexicon against which the pattern is matchrd. The word which obtains the highest average plansihility per character is labeled as the recogni7rtl onr. This method was applied with success on continuous sprrch rrrognition by [5]
Keyword: [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL]
URL: https://hal.inria.fr/inria-00533959
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11
Principles and applications of the VINICS continuous-speech recognition system
In: Advanced speech applications. - Berlin : Springer (1994), 226-242
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12
Automatic speech recognition
Corazza, A. (Mitarb.); De Mori, Renato (Mitarb.); Gretter, R. (Mitarb.)...
In: Speech communication. - Amsterdam [u.a.] : Elsevier 13 (1993) 1-2, 163-205
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13
Non-linear vector interpolation by neural network for phoneme identification in continuous speech
In: https://hal.inria.fr/inria-00075104 ; [Research Report] RR-1457, INRIA. 1991 (1991)
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