THE INTONATION OF TEXTUAL ANOMALIES IN TEXT-TO-SPEECH

This paper examines the intonational characteristics of a number of types of non-word, e.g. numbers, dates, times and other abbreviations, which occur in text and are readily identifiable. These phenomena are often treated as problems for text-to-speech systems, but we take the view that the ease with which they can be identified and the relative predictability of their semantic or pragmatic content makes their intonational behaviour more regular and therefore easier to model than the behaviour of other areas of text. Examples of such phenomena are presented, and heuristics for their treatment by an automatic system are proposed. A formal evaluation of these heuristics is presented, showing a success rate of over 94%. A final discussion outlines the advantages and disadvantages of such a treatment, and suggests lines of future research.