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Word topic models for spoken document retrieval and transcription
Berlin Chen
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Corresponding author for this work
Department of Computer Science and Information Engineering
Research output
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Contribution to journal
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Article
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peer-review
37
Citations (Scopus)
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Dive into the research topics of 'Word topic models for spoken document retrieval and transcription'. Together they form a unique fingerprint.
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Social Sciences
Documents
100%
Transcription
100%
Experiments
66%
Information Retrieval
66%
Language Modeling
66%
Performance
33%
Problem
33%
Buildings
33%
Comparison
33%
History
33%
Chinese
33%
Languages
33%
Information
33%
Semantics
33%
Communities
33%
News Flow
33%
Vocabularies
33%
Alternative
33%
Search
33%
Research Topic
33%
Language Processing
33%
Information Retrieval System
33%
Speech Recognition
33%
INIS
information retrieval
100%
document retrieval
100%
transcription
100%
speech
66%
modeling
66%
probabilistic estimation
66%
taiwan
33%
performance
33%
comparative evaluations
33%
information
33%
communities
33%
china
33%
retrieval systems
33%
humans
33%
capture
33%
processing
33%
natural language
33%
Psychology
Research
100%
Semantics
100%
Humans
100%
Natural Language
100%
Computer Science
Models
100%
Document Retrieval
100%
Information Retrieval
25%
Natural Languages
12%
Vocabulary
12%
Experimental Result
12%
Semantics
12%
Research Topic
12%
Analysis Model
12%
Structure Model
12%
Information Retrieval Systems
12%
Speech Processing
12%
Broadcast News
12%
Probabilistic Framework
12%