An Algorithm for High Accuracy Name Pronunciation by Parametric Speech Synthesizer

Automatic and accurate pronunciation of personal names by parametric speech synthesizer has become a crucial limitation for applications within the telecommunications industry, since the technology is needed to provide new automated services such as reverse directory assistance (number to name). Within text-to-speech technology, however, it was not possible to offer such functionality. This was due to the inability of a text-to-speech device optimized for a specific language (e.g., American English) to accurately pronounce names that originate from very different language families. That is, a telephone book from virtually any section of the country will contain names from scores of languages as diverse as English and Mandarin, French and Japanese, Irish and Polish. All such non-Anglo-Saxon names have traditionally been mispronounced by a speech synthesizer resulting in gross errors and unintelligible speech. This paper describes how an algorithm for high accuracy name pronunciation was implemented in software based on a combination of cryptanalysis, statistics, and linguistics. The algorithm behind the utility is a two-stage procedure: (1) the decoding of the name to determine its etymological grouping; and (2) specific letter-to-sound rules (both segmental rules as well as stress-assignment rules) that provide the synthesizer parameters with sufficient additional information to accurately pronounce the name as would a typical speaker of American English. Default language and thresholds are settable parameters and are also described. While the complexity of the software is invisible to applications writers as well as users, this functionality now makes possible the automation of highly accurate name pronunciation by parametric speech synthesizer.