Speech-activated text retrieval system for multimodal cellular phones

The paper describes an on-line manual page retrieval system activated by spoken queries for multimodal cellular phones. The system recognizes a user's naturally spoken queries by telephone LVCSR and searches an on-line manual with a retrieval module on a server. The user can view the retrieved data on the screen of the phone via Web access. The LVCSR module consists of a telephone acoustic model and an n-gram language model derived from a task query corpus. The adaptation method using the target manual is also presented. The retrieval module utilizes pairs of words with dependency relations and also distinguishes affirmative and negative expressions to improve precision. The proposed system gives 82.6% keyword recognition accuracy and 77.5% task achievement rate. The field trial of the system is now underway.