Titlebook: New Approaches to Problems in Liquid State Theory; Inhomogeneities and Carlo Caccamo,Jean-Pierre Hansen,George Stell Book 1999 Springer Sc

Genetics

LAP

G. Stellact representation of a speaker utterance extracted from a low dimensional total variability subspace. Although current speaker recognition systems achieve very good results in clean training and test conditions, the performance degrades considerably in noisy environments. The compensation of the no

徹底明白

F. Ladoentifica-tion of rhyme schemes in hip hop lyrics, which to the best of our knowledge, is the first such effort. Unlike previous approaches that use supervised or semi-supervised approaches for the task of rhyme scheme identification, our model does not assume any prior phonetic or labeling informati

過份

G. Parisised, each speech segment is described with a set of contextual features. These contextual features correspond to linguistic, phonetic and prosodic information that may affect the pronunciation of the segments. Gemination and vowel quantity (short vowel vs. long vowel) are two particular and importan

NOVA

流出

遍及

破譯

B. Groh,S. Dietricha recorded in noisy and reverberant conditions is extremely limited, especially compared to the amount of data that can be . by adding noise to clean annotated speech. Thus, using both real and simulated data is important in order to improve robust speech recognition. Another promising method applie

Dysplasia

S. Dietrichoften requires annotating in-domain data from scratch, as there is usually a lack of annotated resources for such scenarios. In this work, knowledge from a classifier learnt from a source annotated dataset is transferred to speed up the process of training a binary personal data identification class

美食家

M. L. Rosinberguage processing. In addition, most of the work in this domain addresses the English language because of the high availability of annotated training data compared to other languages. Therefore, we investigate methods for image captioning in German that transfer knowledge from English training data. W