Phonetic-distance-based hypothesis driven lexical adaptation for transcribing multlingual broadcast news
Petra Geutner, Michael Finke, Alex Waibel · 1998
High out-of-vocabulary (OOV) rates are one of the most prevailing problems for languages with a rapid vocabulary growth due to a large number of inflections. Especially when transcribing SerboCroatian and German broadcast news, the OOV-rate is between 8.7% and 4.5%. Hypothesis Driven Lexical Adaptation (HDLA) has already been shown to decrease high OOV-rates significantly by using morphology-based linguistic knowledge. This paper introduces another approach to dynamically adapt a recognition lexicon to the utterance to be recognized. Instead of morphological knowledge about word stems and inflection endings, distance measures based on Levenstein distance are used. Results based on phoneme and grapheme distances will be presented. Compared to the use of morphological knowledge, our distance-based approach offers the distinct advantage that no expert knowledge about a specific language is required, no definition of complex grammar rules is necessary. Instead, grapheme sequences or the ph...