Phoneme-to-grapheme Conversion for Out-of-vocabulary Words in Large Vocabulary Speech Recognition

In this paper, we describe a method to enhance the readability of the textual output in a large vocabulary continuous speech recognition system when out-of-vocabulary words occur. The basic idea is to replace uncertain words in the transcriptions with a phoneme recognition result that is postprocessed using a phoneme-to-grapheme converter. This converter turns phoneme strings into grapheme strings and is trained using machine learning techniques. Experiments show that, even when the grapheme strings are not fully correct, the resulting transcriptions are more easily readable than the original ones.