In this paper, we study the fast adaptation problem of n-gram language model under the MAP estimation framework. We have proposed a heuristic method to explore inter-word correlation to accelerate MAP adaptation of n-gram model. According to their correlations, the occurrence of one word can be used to predict all other words in adaptation text. In this way, a large n-gram model can be efficien...

This paper deals with unsupervised model adaptation for speaker recognition. Two adaptation schemes are proposed, the first one is based on a test by test model adaptation and the second one proposes a batch mode, where the adaptation is performed using a set of tests before computing the decision score for each of them. The experiments are conducted thanks to the NIST SRE 2005 database. This p...

the present study is an attempt to analyze the characters in the novel blindness and its cinematic adapta- tion from intersemiotic viewpoint. to this end, the researchers provided a synthesized model, which is a combination of bernando (2012) and forster's (1927) classification of characters in order to analyze the two main characters from intersemiotic viewpoint. considering the differenc...

This paper proposes a method to automatically extract keywords from baseball radio speech through LVCSR for highlight scene retrieval. For robust recognition, we employed acoustic and language model adaptation. In acoustic model adaptation, supervised and unsupervised adaptations were carried out using MLLR+MAP. By this two level adaptation, word accuracy was improved by 28%. In language model ...