Probabilistic latent topic models have recently enjoyed much success in extracting and analyzing latent topics in text in an unsupervised way. One common deficiency of existing topic models, though, is that they would not work well for extracting cross-lingual latent topics simply because words in different languages generally do not co-occur with each other. In this paper, we propose a way to ...

In this paper we introduce the idea of cross-lingual emotion transplantation. The aim is to lean the nuances of emotional speech in a source language for which we have enough data to adapt an acceptable quality emotional model by means of CSMAPLR adaptation, and then convert the adaptation function so it can be applied to a target language in a different target speaker while maintaining the spe...

Discourse parsing is an integral part of understanding information flow and argumentative structure in documents. Most previous research has focused on inducing and evaluating models from the English RST Discourse Treebank. However, discourse treebanks for other languages exist, including Spanish, German, Basque, Dutch and Brazilian Portuguese. The treebanks share the same underlying linguistic...

The aim of this work is to exploit the acoustic-phonetic similarities between several languages. In recent work cross{ language HMM-based phoneme models have been used only for bootstrapping the language{dependent models and the multi{lingual approach has been investigated only on very small speech corpora. In this paper, we introduce a statistical distance measure to determine the similarities...