Method:
raw speech signal into CNN -> learns salient features for ASR;
analysis of what is learnt -> CNN models phone-specific spectral envelope information
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%0 Conference Paper
%1 palaz2015analysis
%A Palaz, Dimitri
%A Collobert, Ronan
%A others,
%B Proceedings of Interspeech
%D 2015
%K Automatic CNN, TIMIT raw recognition, signal, speech
%T Analysis of cnn-based speech recognition system using raw speech as input
%Z Method:
raw speech signal into CNN -> learns salient features for ASR;
analysis of what is learnt -> CNN models phone-specific spectral envelope information
@inproceedings{palaz2015analysis,
added-at = {2018-02-19T14:58:22.000+0100},
annote = {Method:
raw speech signal into CNN -> learns salient features for ASR;
analysis of what is learnt -> CNN models phone-specific spectral envelope information},
author = {Palaz, Dimitri and Collobert, Ronan and others},
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biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28d432f872b56b4dfe35acfd2daa84745/michaelneumann},
booktitle = {Proceedings of Interspeech},
date-added = {2016-07-13 13:52:07 +0000},
date-modified = {2017-02-21 12:22:17 +0000},
interhash = {832d689a0226d54954717bfeae4f6c6d},
intrahash = {8d432f872b56b4dfe35acfd2daa84745},
keywords = {Automatic CNN, TIMIT raw recognition, signal, speech},
timestamp = {2018-02-19T13:58:22.000+0100},
title = {Analysis of cnn-based speech recognition system using raw speech as input},
year = 2015
}