Recognition of Chinese names in continuous speech for directory assistance applications

The issue of this paper is to enable continuous speech input for directory assistance tasks. We are focusing on handling of long lists of Chinese names. Compared with the more restrictive isolated word input scenario the name error rate for the continuous task is much larger. By concentrating on the name segment, we investigate two methods in order to bridge the performance gap. First, a confidence measure-based rescoring approach to pickup the most confident name is presented. Then, a segmentation-based two-pass method, first estimating the time segmentation of the name and secondly, applying the isolated word recognition technique is studied. The obtained results for both methods reveal a significant name recognition error rate reduction by up to 42% relatively.