A Speech Input Query System for Chinese Web Page Based on VenusDictate

• Main Authors: Chen, Shih-DA, 陳世達
• Other Authors: Jhing-Fa Wang
• Format: Others
• Language: zh-TW
• Published: 1998
• Online Access: http://ndltd.ncl.edu.tw/handle/34672832225858800335

碩士 === 國立成功大學 === 電機工程學系 === 86 === In this thesis, a Speech Input Query System for Chinese Web Page is described. The user can query data on web page using speech input. This query system includes a network part, a language model part, a speech recognition part and a query part.In network part, the system can get web page dynamically and build keyword model of the web page. The language model part deals with the ambiguity in segmenting sentence by Viterbi algorithm. It caculates unigram and bigram information from vocabularies of web pages, and builds common vocabularies of web pages from query sentence. In the speech recognition part, we use VenusDictate as the recognition kernel.It first builds character-lattice and word-lattice using vocabularies and common vocabularies of web pages, then finds the optimal word sequence using full search and BIGRAM language model. In addition, we propose a grammar rule and modifies part of BIGRAM language model in order to speed up recognition time and increase recognition rate. In query part, the system offers many syntax for query, and the result can be displayed on web brower or output by a TTS system.We use web page on NCKU EE and NCKU IIE for test, and design 100 query sentences and 100 keywords for expriments. The recognition rate and recognition time depends on the size of web page. Experimental results show that the top one recognition rate is 93.1%, top ten recognition rate is 100%, and the average recogniton time is 0.23 second.