Lexical Choice via Topic Adaptation for Paraphrasing Written Language to Spoken Language

Our research aims at developing a system that paraphrases written language text to spoken language style. In such a system, it is important to distinguish between appropriate and inappropriate words in an input text for spoken language. We call this task lexical choice for paraphrasing. In this paper, we describe a method of lexical choice that considers the topic. Basically, our method is based on the word probabilities in written and spoken language corpora. The novelty of our method is topic adaptation. In our framework, the corpora are classified into topic categories, and the probability is estimated using such corpora that have the same topic as input text. The result of evaluation showed the effectiveness of topic adaptation.

• Type: Conference
• Year: 2005
• Where: IJCNLP
• Authors: Nobuhiro Kaji, Sadao Kurohashi
• Keywords: IJCNLP 2005, Input Text, Lexical Choice, Natural Language Processing, Spoken Language