Paraphrasing Predicates from Written Language to Spoken Language Using the Web

Paraphrasing Predicates from Written Language to Spoken Language Using the Web Nobuhiro Kaji and Masashi Okamoto and Sadao Kurohashi Graduate School of Information Science and Technology, the University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan �kaji,okamoto,kuro �@kc.t.u-tokyo.ac.jp Abstract There are a lot of differences between expres- sions used in written language and spoken lan- guage. It is one of the reasons why speech syn- thesis applications are prone to produce unnat- ural speech. This paper represents a method of paraphrasing unsuitable expressions for spo- ken language into suitable ones. Those two expressions can be distinguished based on the occurrence probability in written and spoken language corpora which are automatically col- lected from the Web. Experimental results indi- cated the effectiveness of our method. The pre- cision of the collected corpora was 94%, and the accuracy of learning paraphrases was 76 %. 1 Introduction Information can be provided in various forms, and one of them is speech form. Speech form is familiar to humans, and can convey information effectively (Nadamoto et al., 2001; Hayashi et al., 1999). However, little electronic information is provided in speech form so far. On the other hand, there is a lot of information in text form, and it can be transformed into speech by a speech synthesis. Therefore, a lot of attention has been given to applications which uses speech synthesis, for example (Fukuhara et al., 2001). In order to enhance such applications, two problems need to be resolved. The first is that current speech syn- thesis technology is still insufficient and many applica- tions often produce speech with unnatural accents and in- tonations. The second one is that there are a lot of differ- ences between expressions used in written language and spoken language. For example, Ohishi indicated that dif- ficult words and compound nouns are more often used in written language than in spoken language (Ohishi, 1970). Therefore, the applications are prone to produce unnatu- ral speech, if their input is in written language. Although the first problem is well-known, little atten- tion has been given to the second one. The reason why the second problem arises is that the input text contains Un- suitable Expressions for Spoken language (UES). There- fore, the problem can be resolved by paraphrasing UES into Suitable Expression for Spoken language (SES). This is a new application of paraphrasing. There are no similar attempts, although a variety of applications have been discussed so far, for example question-answering (Lin and Pantel, 2001; Hermjakob et al., 2002; Duclaye and Yvon, 2003) or text-simplification (Inui et al., 2003). (1) Written (2) Spoken (3) Unnatural Figure 1: Paraphrasing UES into SES Figure 1 illustrates paraphrasing UES into SES. In the figure, three types of expressions are shown: (1) expres- sions used in written language, (2) expressions used in spoken language, and (3) unnatural expressions. The overlap between two circles represents expressions used both in written language and spoken language. UES is the shaded portion: unnatural expressions, and expres- sions used only in …

Content truncated to 500 words