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0707
Speech recognition; Speaker adaptation; Hidden Markov model;
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Speech recognition; Gaussian mixture model; Duration distribution based
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Automatic speech recognition; Hidden Markov models; Adaptation;
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0810
BibRef
Earlier: A1, A3, Only:
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IEEE DOI
0409
Type-2 fuzzy sets; Gaussian mixture models; Hidden Markov models
BibRef
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Sequence learning; EM algorithm; Wavelets; Speech recognition
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Augmented speech; Electro-Magnetic Articulography (EMA); Automatic
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1101
Minimum classification error; Principal Component Analysis; Linear
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Jean, F.R.,
Adaptation of Hidden Markov Models for Recognizing Speech of Reduced
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1312
hidden Markov models
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Cho, J.W.,
Park, H.M.,
An Efficient HMM-Based Feature Enhancement Method With Filter
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1311
Bayes methods
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Chung, Y.J.[Yong-Joo],
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Noisy speech recognition
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1710
Hidden Markov models, Mel frequency cepstral coefficient, Speech,
Speech recognition, Training, Acoustic mismatch,
pitch-adaptive features, prosody modification,
speech recognition, zero-frequency, filter
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Baltruaitis, T.[Tadas],
Ahuja, C.,
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Multimodal Machine Learning: A Survey and Taxonomy,
PAMI(41), No. 2, February 2019, pp. 423-443.
IEEE DOI
1901
Speech recognition, Visualization, Media, Speech,
Multimedia communication, Streaming media, Hidden Markov models,
survey
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Hsiao, R.,
Can, D.,
Ng, T.,
Travadi, R.,
Ghoshal, A.,
Online Automatic Speech Recognition With Listen, Attend and Spell
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SPLetters(27), 2020, pp. 1889-1893.
IEEE DOI
2011
Hidden Markov models, Decoding, Training, Earth Observing System,
Computational modeling, Acoustics, Automatic speech recognition,
online recognition
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Qiu, J.Y.[Jia-Yan],
Wang, X.C.[Xin-Chao],
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Matching Seqlets: An Unsupervised Approach for Locality Preserving
Sequence Matching,
PAMI(43), No. 2, February 2021, pp. 745-752.
IEEE DOI
2101
Hidden Markov models, Task analysis, Annotations, Pattern matching,
Speech recognition, Optimization, Coherence, Sequence matching,
joint optimization
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de Souza, D.B.[Douglas Baptista],
Bakri, K.J.[Khaled Jamal],
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Multitaper-Mel Spectrograms for Keyword Spotting,
SPLetters(29), 2022, pp. 2028-2032.
IEEE DOI
2210
Spectrogram, Hidden Markov models, Feature extraction,
Speech recognition, Internet, Computational modeling, Training,
mel spectrograms
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Shahin, M.,
Ji, J.X.,
Ahmed, B.,
One-Class SVMs Based Pronunciation Verification Approach,
ICPR18(2881-2886)
IEEE DOI
1812
Feature extraction, Hidden Markov models, Training,
Support vector machines, Error analysis, Lattices, Acoustics,
speech attributes
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Addarrazi, I.,
Satori, H.,
Satori, K.,
Amazigh audiovisual speech recognition system design,
ISCV17(1-5)
IEEE DOI
1710
Face, Feature extraction, Hidden Markov models, Lips, Mouth,
Speech recognition, Visualization, Audio-visual recognition,
Automatic Speech Recognition, HMM, lip, reading
BibRef
Wu, C.,
Ng, R.W.M.,
Torralba, O.S.,
Hain, T.,
Analysing acoustic model changes for active learning in automatic
speech recognition,
WSSIP17(1-5)
IEEE DOI
1707
Acoustics, Adaptation models, Analytical models,
Computational modeling, Data models, Hidden Markov models,
Measurement, Active learning, confidence measures, data selection,
speaker, adaptation
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Asadullah,
Shaukat, A.,
Ali, H.,
Akram, U.,
Automatic Urdu Speech Recognition using Hidden Markov Model,
ICIVC16(135-139)
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1610
cepstral analysis
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Conka, D.,
Viszlay, P.,
Juhár, J.,
Fuzzy clustering in HMM-based triphone classes of 2DLDA in Slovak
LVCSR,
WSSIP16(1-4)
IEEE DOI
1608
fuzzy set theory
BibRef
Kacur, J.,
Kozicka, R.,
Vargic, R.,
Semi-tight covariance matrices implementation in MASPER HMM training
procedure,
WSSIP16(1-4)
IEEE DOI
1608
covariance matrices
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Kacur, J.,
Trnovsky, T.,
Vargic, R.,
Discriminative training of HMM using MASPER procedure,
WSSIP15(93-96)
IEEE DOI
1603
hidden Markov models
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Pérez Maldonado, Y.[Yara],
Caballero Morales, S.O.[Santiago Omar],
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GA Approaches to HMM Optimization for Automatic Speech Recognition,
MCPR12(313-322).
Springer DOI
1208
BibRef
Swietojanski, P.[Pawel],
Wielgat, R.[Robert],
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Automatic Selection of Pareto-Optimal Topologies of Hidden Markov
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EvoIASP11(224-233).
Springer DOI
1104
Applied to speech recognition.
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Ravinder, K.[Kumar],
Comparison of HMM and DTW for Isolated Word Recognition System of
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CIARP10(244-252).
Springer DOI
1011
BibRef
Duan, Q.S.[Quan-Sheng],
Kang, S.Y.[Shi-Yin],
Wu, Z.Y.[Zhi-Yong],
Cai, L.H.[Lian-Hong],
Shuang, Z.W.[Zhi-Wei],
Qin, Y.[Yong],
Comparison of Syllable/Phone HMM Based Mandarin TTS,
ICPR10(4496-4499).
IEEE DOI
1008
BibRef
Kacur, J.,
Rozinaj, G.,
Adding Voicing Features into Speech Recognition Based on HMM in Slovak,
WSSIP09(1-4).
IEEE DOI
0906
BibRef
Kruger, S.E.[Sven E.],
Schaffoner, M.[Martin],
Katz, M.[Marcel],
Andelic, E.[Edin],
Wendemuth, A.[Andreas],
Mixture of Support Vector Machines for HMM based Speech Recognition,
ICPR06(IV: 326-329).
IEEE DOI
0609
BibRef
Andelic, E.[Edin],
Schaffoner, M.[Martin],
Katz, M.[Marcel],
Kruger, S.E.[Sven E.],
A Hybrid HMM-Based Speech Recognizer Using Kernel-Based Discriminants
as Acoustic Models,
ICPR06(II: 1158-1161).
IEEE DOI
0609
BibRef
Demirekler, M.,
Karahan, F.,
Ciloglu, T.,
Fusing length and voicing information, and HMM decision using a
Bayesian causal tree against insufficient training data,
ICPR00(Vol III: 102-105).
IEEE DOI
0403
BibRef
Steidl, S.[Stefan],
Stemmer, G.[Georg],
Hacker, C.[Christian],
Nöth, E.[Elmar],
Niemann, H.[Heinrich],
Improving Children's Speech Recognition by HMM Interpolation with an
Adults' Speech Recognizer,
DAGM03(600-607).
Springer DOI
0310
BibRef
Nouza, J.,
Feature selection methods for hidden Markov model-based speech
recognition,
ICPR96(II: 186-190).
IEEE DOI
0509
BibRef
Rieck, S.,
Schukat-Talamazzini, E.G.,
Niemann, H.,
Speaker adaptation using semi-continuous hidden Markov models,
ICPR92(III:541-544).
IEEE DOI
9208
BibRef
Chapter on New Unsorted Entries, and Other Miscellaneous Papers continues in
Speech Recognition, Neural Networks, CNN .