The results from applying an improved algorithm in the task of automatic segmentation of spontaneoustelephone quality speech are presented , and compared to the results from those resulting from superimposing white noise. Three segmentation algorithms are compared which are all based on variants of the Spectral Variation Function. Experimental results are… (More)
Slovenian language is among the richest Slavic languages in view of the number of dialects. More than 40 dialects in seven dialect groups can be found on a territory of about 21,000 km 2 and population of 2 million. Given the richness of influencing factors on the Standard Slovenian language we decided to undertake an acoustic analysis of its contemporary… (More)
We present a large vocabulary, continuous speech recognition system based on Linked Predictive Neural Networks (LPNN's). The system uses neu-ral networks as predictors of speech frames, yielding distortion measures which are used by the One Stage DTW algorithm to perform continuous speech recognition. The system, already deployed in a Speech to Speech… (More)
This paper reports on results from ongoing research on language-identification (LID) performed on the three languages: American-English, German and Spanish. The speech material used is from the Oregon Graduate Institute Spontaneous Telephone Speech Corpus, OGI_TS. The baseline LID-system consists of three parallel phoneme recognisers each of which are… (More)
We present a context-dependent, phoneme and function word based, Hidden Control Neural Network (HCNN-CDF) architecture for continuous speech recognition. The system can be seen as a large vocabulary extension of the word-based HCNN system proposed by Levin in 1990. Initially, we analysed context-/ndependent HCNN modeling principle in the framework of the… (More)
This paper summarizes the rationale for proposing the COST-277 " nonlinear speech processing " action, and the work done during these last four years. In addition, future perspectives are described.
τ Socrates/Erasmus exchange student under the multilateral agreement UL D-IV-1/99-JM/Kc. Abstract Though the Slovenian SpeechDat(II) database is the largest spoken language resources for Slovenian ever recorded, it belongs to the smaller speech data collections made available by the European LE2-4001 project (http://www.speechdat.org/). The aim of this… (More)