Conditional Drums Generation Using Compound Word Representations

Spanish NER with Word Representations and Conditional Random Fields

Word Representations such as word embeddings have been shown to significantly improve (semi-)supervised NER for the English language. In this work we investigate whether word representations can also boost (semi-)supervised NER in Spanish. To do so, we use word representations as additional features in a linear chain Conditional Random Field (CRF) classifier. Experimental results (82.44 Fscore ...

Automatic Generation of Compound Word Lexicon for Hindi Speech Synthesis

This paper addresses the problem of Hindi compound word splitting and its relevance to developing a good quality phonetizer for Hindi Speech Synthesis. The constituents of a Hindi compound word are not separated by space or hyphen. Hence, most of the existing compound splitting algorithms can not be applied to Hindi. We propose a new technique for automatic extraction of compound words from Hin...

Learning Word Vectors Efficiently Using Shared Representations and Document Representations

Compound Key Word Generation from Document Databases Using A Hierarchical Clustering ART Model

The growing availability of databases on the information highways motivates the development of new processing tools able to deal with a heterogeneous and changing information environment. A highly desirable feature of data processing systems handling this type of information is the ability to automatically extract its own key words. In this paper we address the specific problem of creating sema...

Modelling Word Meaning using Efficient Tensor Representations

Models of word meaning, built from a corpus of text, have demonstrated success in emulating human performance on a number of cognitive tasks. Many of these models use geometric representations of words to store semantic associations between words. Often word order information is not captured in these models. The lack of structural information used by these models has been raised as a weakness w...