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A large-scale classification of English verbs
TLDR
Lexical classifications have proved useful in supporting various natural language processing (NLP) tasks. Expand
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Extending VerbNet with Novel Verb Classes
TLDR
Korhonen and Briscoe (2004) proposed a significant extension of Levin’s classification which incorporates 57 novel classes for verbs not covered (comprehensively) by Levin. Expand
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Speech activity detection on youtube using deep neural networks
TLDR
We demonstrate that a DNN with input consisting of multiple frames of mel frequency cepstral coefficients (MFCCs) yields drastically lower frame-wise error rates (19.6%) on YouTube videos compared to a conventional GMM based system (40%). Expand
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From Light to Rich ERE: Annotation of Entities, Relations, and Events
TLDR
We describe the evolution of the Entities, Relations and Events (ERE) annotation task, created to support research and technology development within the DARPA DEFT program. Expand
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A Large-scale Classication of English Verbs
TLDR
Korhonen and Briscoe (2004) have proposed a signicant extension of Levin's classication which incor- porates 57 novel classes for verbs not covered (comprehensively) by Levin. Expand
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The Second DIHARD Diarization Challenge: Dataset, task, and baselines
TLDR
This paper introduces the second DIHARD challenge, the second in a series of speaker diarization challenges intended to improve the robustness of speech-to-text systems to variation in recording equipment, noise conditions, and conversational domain. Expand
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Automatic phonetic segmentation using boundary models
TLDR
This study attempts to improve automatic phonetic segmentation within the HMM framework. Expand
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Binding of Anaphors in LTAG
TLDR
This paper presents an LTAG account of the syntax and semantics of anaphoric expressions that covers basic binding as well as raising, ECM, and extraction data. Expand
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Assigning XTAG Trees to VerbNet
TLDR
This paper presents the mappings between the syntactic information of our broad-coverage domain-independent verb lexicon, VerbNet, and a syntactically rich lexical resource, the Xtag grammar. Expand
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Mandarin tone classification without pitch tracking
TLDR
A deep neural network (DNN) based classifier achieved 27.62% segment error rate (SER) in recognizing five tonal categories in Mandarin Chinese broadcast news, based on 40 mel-frequency cepstral coefficients (MFCCs). Expand
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