Functional Mapping of Inner Speech Areas: A Preliminary Study with Portuguese Speakers
Authors
Abstract
We present our first results in applications of recurrent neural networks to Russian. The problem of re-scoring of equiprobable hypotheses has been solved. We train several recurrent neural networks on a lemmatized news corpus to mitigate the problem of data sparseness. We also make use of morphological information to make the predictions more accurate. Finally we train the Ranking SVM model and show that combination of recurrent neural networks and morphological information gives better results than 5-gram model with Knesser-Ney discounting.
Keywords
music coding,opus,spectral features,surround sound
Conference
SPECOM 2018 - International Conference on Speech and Computer 2018
DOI
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