Abstract
This paper discusses the usage of feed-forward and recurrent Artificial Neural Networks (ANNs) in whole word speech recognition. The Long-Short Term Memory (LSTM) network has been trained to do speaker independent recognition of any series of connected digits in polish language, using only the acoustic features extracted from speech. It is also shown how to effectively change the analog network output into binary information on recognized words. The parametrs of the conversion are fine-tuned using artificial evolution.
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Brocki, Ł., Koržinek, D., Marasek, K. (2006). Recognizing Connected Digit Strings Using Neural Networks. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2006. Lecture Notes in Computer Science(), vol 4188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846406_43
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DOI: https://doi.org/10.1007/11846406_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-39090-9
Online ISBN: 978-3-540-39091-6
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