State Sequence Modeling
State Sequence Modeling is a computational framework within sequence pattern recognition that characterizes temporal dynamics by representing system behaviors as transitions among discrete states, distinguished by its explicit modeling of state dependencies and emission processes in sequential data.
181
Publications
9.3K
Citations
534
Authors
239
Institutions
Publications per year
2017–2026
55
Parents
181
Speech parameter generation algorithms for HMM-based speech synthesis
Keiichi Tokuda, Takayoshi Yoshimura, Takashi Masuko et al. · 2002 · 1K citations
Oversampled Sigma-Delta Modulation
Robert M. Gray · IEEE Transactions on Communications · 1987 · 354 citations
Reconstruction Network for Video Captioning
Bairui Wang, Lin Ma, Wei Zhang et al. · 2018 · 336 citations
An HDP-HMM for systems with state persistence
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan et al. · 2008 · 272 citations · Full text
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Massachusetts Institute of Technology
Cambridge, United States
6 h-index
12 publications
875 citations
AT&T (United States)
Bedminster, United States
5 h-index
12 publications
273 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
10 publications
479 citations
University of Cambridge
Cambridge, United Kingdom
5 h-index
10 publications
372 citations
Tokyo Institute of Technology
Tokyo, Japan
5 h-index
11 publications
3.2K citations

Nagoya Institute of Technology
Nagoya, Japan
5 h-index
15 publications
4.1K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
4 h-index
7 publications
241 citations
University of California, Berkeley
Berkeley, United States
4 h-index
7 publications
871 citations
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Repository · 8 publications · 230 citations
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4 publications · 128 citations
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4 publications · 119 citations
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3 publications · 203 citations
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3 publications · 86 citations
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