Título:
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Using dependency parsing and machine learning for factoid question answering on spoken documents
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Autor/a:
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Comas Umbert, Pere Ramon; Turmo Borras, Jorge; Màrquez Villodre, Lluís
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Otros autores:
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Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics; Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural |
Abstract:
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This paper presents our experiments in question answering for speech corpora. These experiments focus on improving the answer extraction step of the QA process. We present two approaches to answer extraction in question answering for speech corpora that apply machine learning to improve the coverage and precision of the extraction. The first one is a reranker that uses only lexical information, the second one uses dependency parsing to score robust similarity between syntactic structures. Our experimental results show that the proposed learning models improve our previous results using only hand-made ranking rules with small syntactic information. Moreover, this results show also that a dependency parser can be useful for speech transcripts even if it was trained with written text data from a
news collection. We evaluate the system on manual transcripts of speech from EPPS English corpus and a set of questions transcribed from spontaneous oral questions. This data belongs to the CLEF 2009 track on QA on speech transcripts (QAst). |
Abstract:
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Peer Reviewed |
Materia(s):
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural -Speech transcripts -Question answering -Natural language processing (Computer science) -Tractament del llenguatge natural (Informàtica) |
Derechos:
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Tipo de documento:
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Artículo - Versión presentada Objeto de conferencia |
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