Automatic modeling for adding new words to a large-vocabulary continuous speech recognition system

The authors report on the detection of new words for the speaker-dependent and speaker-independent paradigms. A useful operating point in a speaker-dependent paradigm is defined at 71% detection rate and 1% false alarm rate. The authors present a novel technique for obtaining a phonetic transcription for a new word, which is needed to add the new word to the system. The technique utilizes DECtalk's text-to-sound rules to obtain an initial phonetic transcription for the new word. Since these text-to-sound rules are imperfect, a probabilistic transformation technique is used that produces a phonetic pronunciation network of all possible pronunciations given DECtalk's transcription. The network is used to constrain a phonetic recognition process that results in an improved phonetic transcription for the new word. The resulting transcriptions are sufficient for speech recognition purposes.<<ETX>>