Improving proper name recognition by adding automatically learned pronunciation variants to the lexicon Universiteit Gent
This paper deals with the task of large vocabulary proper name recognition. In order to accomodate a wide diversity of possible name pronunciations (due to non-native name origins or speaker tongues) a multilingual acoustic model is combined with a lexicon comprising 3 grapheme-to-phoneme (G2P) transcriptions (from G2P transcribers for 3 different languages) and up to 4 so-called phoneme-to-phoneme (P2P) transcriptions. The latter are generated ...