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A Framework for an Ontology-Driven Multi-Lingual Transcription System with IPA Representation

One of the important issues in computational linguistics is to design systems for speech recognition and machine transcription which can be used for various types of spoken data. In manual as well as in machine transcription in particular, names as such are of great importance when addressing people, locations, and objects. In order to communicate names between language communities with different writing systems we have to transcribe or romanise the names into the corresponding writing systems. Names tend to show a certain intrinsic grade of variation, and this is even more the case for their transliterated or transcribed forms. Correct transcription and transliteration of names is one of the major problems in cross-cultural communication. Available standard manual transcription systems are often used inconsistently, or simply not used at all. Many computer-based transcription systems use orthographic forms or pronunciation, rule based and statistical approaches. In this paper the authors propose an automatic transcription model for multilingual transcription systems. This model uses four advanced methods or tools: (1) a syllable pronunciation and segmentation model with rule based multi-lingual pronunciation, (2) a rule based approach with IPA (International Phonetic Alphabet) representation that is converted to different writing systems, (3) an ontology of phonemes to capture the phonetic qualities of characters for different languages, and (4) a phonetic based name matching algorithm called Meta-Sound (a combination of Metaphone and Soundex algorithms) for constructing the thesaurus of transcriptions to get different name variations of a specific name dynamically. This algorithm is designed for different language specific naming conventions, and it helps to produce highly accurate matches. The model is not only used for romanisation but also for the transcription into other writing systems, e.g. the Thai writing system.