Word Informativeness and Automatic Pitch Accent Modeling

Word Informativeness and Automatic Pitch Accent Modeling Shimei Pan and Kathleen R. McKeown Dept. of Computer Science Columbia University New York, NY 10027, USA {pan, kathy}@cs, columbia, edu Abstract In intonational phonology and speech syn- thesis research, it has been suggested that the relative informativeness of a word can be used to predict pitch prominence. The more information conveyed by a word, the more likely it will be accented. But there are oth- ers who express doubts about such a correla- tion. In this paper, we provide some empiri- cal evidence to support the existence of such a correlation by employing two widely ac- cepted measures of informativeness. Our ex- periments show that there is a positive corre- lation between the informativeness of a word and its pitch accent assignment. They also show that informativeness enables statisti- cally significant improvements in pitch ac- cent prediction. The computation of word informativeness is inexpensive and can be incorporated into speech synthesis systems easily. 1 Introduction The production of natural, intelligible speech remains a major challenge for speech synthesis research. Recent research has focused on prosody modeling (Silverman, 1987; Hirschberg, 1990; Santen, 1992), which determines the variations in pitch, tempo and rhythm. One of the critical issues in prosody modeling is pitch accent assign- ment. Pitch accent is associated with the pitch prominence of a word. For example, some words may sound more prominent than others within a sentence because they are as- sociated with a sharp pitch rise or fall. Usu- ally, the prominent words bear pitch accents while the less prominent ones do not. A1- though native speakers of a particular lan- guage have no difficulty in deciding which words in their utterances should be accented, the general pattern of accenting in a lan- guage, such as English, is still an open ques- tion. Some linguists speculate that relative in- formativeness, or semantic weight of a word can influence accent placement. Ladd (1996) claims that "the speakers assess the relative semantic weight or informativeness of poten- tially accentable words and put the accent on the most informative point or points" (ibid, pg. 175). He also claims that "if we un- derstand relative semantic weight, we will automatically understand accent placement" (ibid, pg. 186). Bolinger (Bolinger, 1972) also uses the following examples to illustrate the phenomenon: 1. "He was arrested because he KILLED a man." 2. "He was arrested because he killed a POLICEMAN." The capitalized words in the examples are accented. In (1), "man" is semantically empty relative to "kill"; therefore, the verb "kill" gets accented. However, in (2), "po- liceman" is semantically rich and is accented instead. However, different theories, not based on informativeness, were proposed to explain the above phenomenon. For example, Bres- nan's (1971) explanation is based on syn- tactic function. She suggests that "man" in the above sentence does not get accented because "man" and other words like "guy" or "person" or "thing" form a category of 148 "semi-pronouns". Counter-examples listed below raise more questions about the …

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