1 Centro de Estudios Avanzados en Zonas Áridas, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile, 2 Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA, 3 Departamento de Ecología, Pontificia Universidad Católica de Chile, Alameda, Chile, 4 Facultad de Ingeniería y Ciencias and Facultad de Artes Liberales, Universida...

1) Institute of Zoology, Slovak Academy of Sciences, Dúbravská cesta 9, SK-84506 Bratislava, Slovakia (e-mail: [email protected]) 2) University of Trnava, Faculty of Education, Department of Biology, Priemyselná 4, P.O. Box 9, SK-91843 Trnava, Slovakia (e-mail: [email protected]) 3) Estación Experimental de Zonas Áridas (CSIC), Departamento de Ecología Funcional y Evolutiva, General S...

In this paper, we adapt the TF-IDF model to the Japanese grapheme-phoneme alignment task, by way of a simple statistical model and an incremental learning method. In the incremental learning method, grapheme-phoneme alignment paradigms are disambiguated one at a t ime according to the relative plausibility of the highest scoring alignment schema, and the statistical model is re-trained accordin...

This paper reports results in building an Egyptian Arabic speech recognition system as an example for under-resourced languages. We investigated different approaches to build the system using 10 hours for training the acoustic model, and results for both grapheme system and phoneme system using MADA. The phoneme-based system shows better results than the grapheme-based system. In this paper, we...

Hidden Markov models (HMMs) have proven useful in various aspects of speech technology from automatic speech recognition through speech synthesis, speech segmentation and grapheme-to-phoneme conversion to part-of-speech tagging. Traditionally, context is modelled at the hidden states in the form of context-dependent models. This paper constitutes an extension to this approach; the underlying co...