ONOMASTICA - Creating a multi-lingual dictionary of European names

I N T R O D U C T I O N The O N O M A S T I C A project was established as part of the "European Commission Framework Programme Linguistic Research and Engineering", with the goal to provide: • a multi-language pronunciation dictionary • letter-to-sound rules • statistics on names, their frequencies and inter-occurrences • self-learning software A total of eleven languages are covered in the project: Danish, Dutch, English, French, German, Greek, Italian, Norwegian, Portuguese, Spanish and Swedish. The 2-year project wi l l not only produce pronunciation dictionaries for up to one million names per language, but w i l l also investigate the problems of exchanging national names amongst the partners to create a matrix of "nativised" pronunciation of foreign names in each language. The multi-lingual dictionary could for example be used in the following sectors: • Telecommunications: Automated directory enquiry systems, telephone banking and enhanced talking newspapers and books for the blind. • Consumer sector: Map information and guidance systems, talking dictionaries and courseware systems for pronunciation teaching. ® Publishing: Hard-copy as well as electronic dictionaries containing pronunciation. The ultimate pronunciation dictionary would include a carefully verified manual transcription of each name, but due to the limited resources only a subset of the name list can be transcribed and verified manually. The names w i l l be divided into three different Quality Bands defined as: B A N D I: Transcriptions judged to be correct to the best of a competent phonetician's knowledge. Transcriptions are guaranteed correct for some owners of the name. B A N D II: Transcriptions judged by a competent phonetician to be acceptable to a native speaker/listener. Names that cannot be easily verified. B A N D III: Transcriptions not yet checked by a competent phonetician. Names that have been transcribed automatically. The names in B A N D I & II wi l l be chosen according to their frequency in the telephone directory so that a cumulative coverage of 80% wi l l be obtained. Each partner has transcribed a "Golden Set" of 40,000 names as part of the project's first phase. Fonetik -94 67 T R A N S C R I P T I O N We are to transcribe personal names, company names, street names and town names, where the company names have been ignored because they are so many and only occur once. Automatic transcription would be very difficult since company names consist of a mix of invented words, foreign words and acronyms. The place names have been manually transcribed with the help of Garlen (1991). We have transcribed the 3100 places included in this book according to our conventions of transcription. The street names often consist of ordinary Swedish words followed by "gatan"(street) or "vagen"(road), ex. Blamesvagen (Blue tit road). They are quite easy to transcribe i f you use a Two-Level morphology (Koskenniemi 1983), with a large lexicon. Our Swedish lexicon consists of 40,000 morphs (Karlsson 1990). Christian names and other first names can be difficult to transcribe since they may have a foreign origin that influences the pronunciation. But fortunately only about 500 names need to be transcribed to obtain a coverage of 80%. However, we have transcribed 6000 names, obtaining a coverage of 95%. The names that can be used in double-names (LarsErik, Anna-Lotta) have been included in the lexicon (920 female and 680 male first names), so that these forms can be generated automatically. The double-names have a very general pronunciation structure: the male are usually three-syllabic and have accent I with stress on the second syllable. The female vary more, but are usually three or foursyllabic and have accent II with primary stress on the first syllable (Kvillerud 1980). Finally, we have the surnames. Since they have been our primary concern, they wil l be described in more detail. S U R N A M E S Until recently we have worked with a name database derived from the Greater Stockholm telephone directory, but we now work with one from the whole of Sweden. The work done with the Stockholm database wi l l be reusable in the future work. When transcribing the surnames automatically the following steps are taken: First, the origin of the names is determined. Then they are processed by different sets of rules depending upon their origin. The process is described in Figure 1. TRANSCRIPTION OF SURNAMES Surname Origin Tagger