Modelling out-of-vocabulary words for robust speech recognition
Issam Bazzi, James Glass · 2002
This thesis concerns the problem of unknown or out-of-vocabulary (OOV) words in continuous speech recognition. We propose a novel approach for handling OOV words within a single-stage recognition framework. To achieve this goal, an explicit and detailed model of OOV words is constructed and then used to augment the closed-vocabulary search space of a standard speech recognizer. This OOV model achieves open-vocabulary recognition through the use of more flexible subword units that can be concatenated during recognition to form new phone sequences corresponding to potential new words. Examples of such subword units are phones, syllables, or some automatically-learned multi-phone sequences. Subword units have the attractive property of being a closed set, and thus are able to cover any new words, and can conceivably cover most utterances with partially spoken words as well. The main challenge with such an approach is ensuring that the OOV model does not absorb portions of the speech signal corresponding to in-vocabulary (IV) words. In dealing with this challenge, we explore several research issues related to designing the subword lexicon, language model, and topology of the OOV model. We present a dictionary-based approach for estimating subword language models. Such language models are utilized within the subword search space to help recognize the underlying phonetic transcription of OOV words. We also propose a data-driven iterative bottom-up procedure for automatically creating a multi-phone subword inventory. Starting with individual phones, this procedure uses the maximum mutual information principle to successively merge phones to obtain longer subword units. The thesis also extends this OOV approach to modelling multiple classes of OOV words. In addition, the thesis examines an approach for combining OOV modelling with recognition confidence scoring. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)