Voice-QA: evaluating the impact of misrecognized words on passage retrieval

Question Answering is an Information Retrieval task where the query is posed using natural language and the expected result is a concise answer. Voice-activated Question Answering systems represent an interesting application, where the question is formulated by speech. In these systems, an Automatic...

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Detalles Bibliográficos
Autores: Calvo Lance, Marcos, Buscaldi, Davide, Rosso, Paolo
Tipo de recurso: capítulo de libro
Fecha de publicación:2012
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/35795
Acceso en línea:https://riunet.upv.es/handle/10251/35795
Access Level:acceso abierto
Palabra clave:Voice-activated question answering
Passage retrieval
Term informativeness
LENGUAJES Y SISTEMAS INFORMATICOS
Descripción
Sumario:Question Answering is an Information Retrieval task where the query is posed using natural language and the expected result is a concise answer. Voice-activated Question Answering systems represent an interesting application, where the question is formulated by speech. In these systems, an Automatic Speech Recognition module can be used to transcribe the question. Thus, recognition errors may be introduced, producing a significant effect on the answer retrieval process. In this work we study the relationship between some features of misrecognized words and the retrieval results. The features considered are the redundancy of a word in the result set and its inverse document frequency calculated over the collection. The results show that the redundancy of a word may be an important clue on whether an error on it would deteriorate the retrieval results, at least if a closed model is used for speech recognition.