Laveraging parallel corpora and existing wordnets for by Darja Fišer (eds)

By Darja Fišer (eds)

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Lookup contact information 6. Open an application 7. Play media 8. g. the subject performs the tasks with the VUI and then performs the same tasks using the GUI; the next subject first performs the tasks with GUI and then performs the same tasks with the VUI). By alternating the interface order independence is gained, breaking any kind of relation between the interfaces that may affect test results. The tests, regarding each interface, are preceded by a four minutes session for interface adaptation.

LTC 2007, LNAI 5603, pp. 36–49, 2009. c Springer-Verlag Berlin Heidelberg 2009 A Study on Bilingual Speech Recognition Involving a Minority Language 37 Acoustic models are also language-dependent because each language defines its own phonemes differently from other languages. In addition, the articulation of shared phonemes may differ in each language. Some work has already been done to find more robust acoustical units for this situation [3]. Therefore, in multilingual systems there is a new difficulty: the system has to determine which language is being spoken.

16 3 S. Drgas and A. Dabrowski Feature Extraction Method by Means of Slope Filtering Block diagram of the proposed feature extraction method is depicted in Fig. 1. Speech signal Preemphasis FFT Slope filtering Mel-scale filterbank DCT Fig. 1. 98. This filter is used in order to equalize the spectrum of the speech signal. Then the signal is divided into frames. These frames do overlap. The length of frames is chosen to assure quasi-stationarity of the signal in each frame (20-25 ms). Next the Hamming window is used and FFT is computed in each frame.

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