We present a new language model adaptation framework integrated with error handling method to improve accuracy of speech recognition and performance of spoken language applications. The proposed error corrective language model adaptation approach exploits domain-specific language variations and recognition environment characteristics to provide robustness and adaptability for a spoken language ...

This paper discuss a dependency analyzer employing Support Vector Machines (SVMs) for Japanese spoken language. Most conventional dependency analyzers target written texts. Thus, we use a currently available spoken language corpus and make the SVMs learn the corpus to build a dependency analyzer that targets spoken language. We used two types of corpora: one contains written language, and the o...

In this paper, we compare the performance of a state-of-the-art statistical parser (Bikel, 2004) in parsing written and spoken language and in generating subcategorization cues from written and spoken language. Although Bikel’s parser achieves a higher accuracy for parsing written language, it achieves a higher accuracy when extracting subcategorization cues from spoken language. Our experiment...

the present paper is the result of the surveys done on the translation of the robaiyyat-e hakim omar khayyam sera'iki language. these translations that are mostly done on the basis of valid and authentic texts both in the persian and english languages, can be divided into two categories: i. translation into prose of the robaiyyat ii. translation into verse of the robaiyyat together with ex...

In this introductory chapter to Part G of this Handbook on spoken language recognition, we provide a brief overview of the principles of state-ofthe-art language recognition approaches, and a general discriminative training framework to improve the performance and robustness of language recognition systems. It is followed by three chapters. The first of these addresses issues related to spoken ...

We present a new language model adaptation framework integrated with an error handling method to improve accuracy of speech recognition and performance of spoken language applications. The proposed error corrective language model (ECLM) adaptation approach exploits recognition environment characteristics and domain-specific semantic information to provide robustness and adaptability for a spoke...