Reliable Unseen Model Prediction for Vocabulary-Independent Speech Recognition

Speech recognition technique is expected to make a great impact on many user interface areas such as toys, mobile phones, PDAs, and home appliances. Those applications basically require robust speech recognition immune to environment and channel noises, but the dialogue pattern used in the interaction with the devices may be relatively simple, that is, an isolated-word type. The drawback of small-vocabulary isolated-word recognizer which is generally used in the applications is that, if target vocabulary needs to be changed, acoustic models should be re-trained for high performance. However, if a phone model-based speech recognition is used with reliable unseen model prediction, we do not need to re-train acoustic models in getting higher performance. In this paper, we propose a few reliable methods for unseen model prediction in flexible vocabulary speech recognition. The first method gives optimal threshold values for stop criteria in decision tree growing, and the second uses an add...

• Type: Conference
• Year: 2004
• Where: AUSAI
• Authors: Sungtak Kim, Hoirin Kim
• Keywords: Artificial Intelligence, AUSAI 2004, Reliable Unseen Models, Speech Recognition, Unseen Model Prediction