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In recent years, trained feature extraction (FE) schemes based on neural networks have replaced or complemented traditional approaches in top performing systems. This paper deals with FE in multilingual scenarios with a target language with low amount of transcribed data. Continuing our previous work on multilingual training of Stacked Bottle-Neck Neural Network FE schemes, we concentrate on improving...
The paper addresses manual and semi-automatic approaches to building a multilingual phoneme set for automatic speech recognition. The first approach involves mapping and reduction of the phoneme set based on IPA and expert knowledge, the later one involves phoneme confusion matrix generated by a neural network. The comparison is done for 8 languages selected from GlobalPhone on three scenarios: 1)...
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