tailieunhanh - Báo cáo khoa học: "A Method for Correcting Errors in Speech Recognition Using the Statistical Features of Character Co-occurrence"

It is important to correct the errors in the results of speech recognition to increase the performance of a speech translation system. This paper proposes a method for correcting errors using the statistical features of character co-occurrence, and evaluates the method. The proposed method comprises two successive correcting processes. The first process uses pairs of strings: the first string is an erroneous substring of the utterance predicted by speech recognition, the second string is the corresponding section of the actual utterance. Errors are detected and corrected according to the database learned from erroneous-correct utterance pairs. . | A Method for Correcting Errors in Speech Recognition Using the Statistical Features of Character Co-occurrence Satoshi Kaki Eiichiro Sumita and Hitoshi lida ATR Interpreting Telecommunications Research Labs Hikaridai 2-2 Seika-cho Soraku-gun Kyoto 619-0288 Japan skaki sumita iida @ Abstract It is important to correct the errors in the results of speech recognition to increase the performance of a speech translation system. This paper proposes a method for correcting errors using the statistical features of character co-occurrence and evaluates the method. The proposed method comprises two successive correcting processes. The first process uses pairs of strings the first string is an erroneous substring of the utterance predicted by speech recognition the second string is the corresponding section of the actual utterance. Errors are detected and corrected according to the database learned from erroneous-correct utterance pairs. The remaining errors are passed to the posterior process which uses a string in the corpus that is similar to the string including recognition errors. The results of our evaluation show that the use of our proposed method as a post-processor for speech recognition is likely to make a significant contribution to the performance of speech translation systems. 1 Introduction In spite of the increased performance of speech recognition systems the output still contains many errors. For language processing such as a machine translation it is extremely difficult to deal with such eưors. In integrating recognition and translation into a speech translation system the development of the following processes is therefore important 1 detection of errors in speech recognition results 2 sorting of speech recognition results by means of error detection 3 providing feedback to the recognition process and or making the user speak again 4 correct errors etc. For this purpose a number of methods have been proposed. One method is to translate correct