Applying of machine learning in the construction of a voice-controlled interface on the example of a music player
Article Sidebar
Open full text
Published:
Dec 30, 2019
Issue Vol. 13 (2019)
Articles
-
Machine Learning as a method of adapting offers to the clients
Jacek Bielecki, Oskar Ceglarski, Maria Skublewska-Paszkowska267-271
-
The insulin activity model based on insulin profiles
Tomasz Nowicki272-278
-
UML – a survey on technical university students in Lublin
Kamil Żyła, Adam Ulidowski, Jan Wrzos, Bartłomiej Włodarczyk, Krzysztof Krocz, Patryk Drozd279-282
-
Overview of Big Data platforms
Gabriel Wróbel, Maciej Daniel Wikira283-287
-
Solutions for managing IT projects in the cloud
Grzegorz Szydlowski288-292
-
Performance analysis of the Symfony framework for creating modern web application based on selected versions
Aleksander Wójcik, Mateusz Wolski, Jakub Bartłomiej Smołka293-297
-
Comparative analysis of databases working under the control of Windows system
Serhii Stets, Grzegorz Kozieł298-301
-
Applying of machine learning in the construction of a voice-controlled interface on the example of a music player
Jakub Basiakowski302-309
-
Application of neural networks to the analysis of consumer opinions
Roman Mysan, Ivan Loichuk, Małgorzata Plechawska-Wójcik310-314
-
Comparative analysis of frameworks dedicated to enterprise designing
Katarzyna Curyła, Karolina Habernal315-322
-
Extraction of parameters from biometric data samples
Paweł Danek, Krzysztof Ćwirta, Piotr Kopniak323-331
-
WebAssembly as an alternative solution for JavaScript in developing modern web applications
Dawid Suryś, Piotr Szłapa, Maria Skublewska-Paszkowska332-338
-
Analysis of the defending possibilities against SQL Injection attacks
Chrystian Byzdra, Grzegorz Kozieł339-344
-
Comparison of 3D games’ efficiency with use of CRYENGINE and Unity game engines
Hubert Żukowski345-348
-
Research of an Entity-component-system architectural pattern designed with using of Data-oriented design technique
Dawid Masiukiewicz, Daniel Masiukiewicz, Jakub Smołka349-353
-
Comparative analysis of Kotlin and Java languages used to create applications for the Android system
Daniel Sulowski, Grzegorz Kozieł354-358
-
A performance comparison of garbage collector algorithms in Java Virtual Machine
Igor Kopeć, Jakub Smołka359-365
-
Innovative applications of digital solutions and tools in educating IT school students
Michalina Gryniewicz-Jaworska366-370
Main Article Content
DOI
Authors
Jakub Basiakowski
jakub.basiakowski@pollub.edu.pl
Lublin University of Technology, Poland
Abstract
The following paper presents the results of research on the impact of machine learning in the construction of a voice-controlled interface. Two different models were used for the analysys: a feedforward neural network containing one hidden layer and a more complicated convolutional neural network. What is more, a comparison of the applied models was presented. This comparison was performed in terms of quality and the course of training.
Keywords:
machine learning; neural network; speech recognition
References
[1] J. Ye, R. J. Povinelli, M. T. Johnson: „Phenome classification using naive Bayes classifier in reconstructed phase space”, IEEE Digital Signal Processing Workshop, 2002
[2] A. Sanchis, A. Juan, E. Vidal: „A Word-Based Naive Bayes Classifier for Confidence Estimation in Speech Recognition”, IEEE Transactions on audio, speech and language processing, vol. 20, NO. 2, 2012
[3] N. Smith, M. Gales: „Speech Recognition using SVMs”, Cambridge University Engineering Dept, 2002
[4] C. Ittichaichareon, S. Suksri, T. Yingthawornsuk: „Speech Recognition using MFCC”, International Conference on Computer Graphics, Simulation and Modeling , 2012
[5] W. M. Campbell, J. P. Campbell, D. A. Reynolds, E. Singer, P. A. Torres-Carrasquillo: „Support vector machines for speaker and language recognition”, Computer Speech and Language 20 210–229, 2006
[6] A. Ganapathiraju, J. E. Hamaker, J. Picone: „Applications of Support Vector Machines to speech recognition”, IEEE Transactions on signal processing, vol 52, NO. 8, 2004
[7] K. Al Smadi, I. Trrad, T. Al Smadi: „ Artificial Intelligence for Speech Recognition Based on Neural Networks”, Journal of Signal and Information Processing, 2015, 6, 66-72, 2015
[8] W. Gevaert, G. Tsenov, V. Mladenov: „Neural networks used for speech recognition”,Journal of automatic control, University of Belgrade, vol. 20:1-7 , 2010
[9] M. Tunckanat, R. Kurban S. Sagiroglu: „Voice Recognition Based On Neural Networks”, IJCI Proceedings of International Conference on Signal Processing, ISSN 1304-2386, Volume:1, Number:2, 2003
[10] A. Ahad, A. Fayyaz, T. Mehmood: „Speech Recognition using Multilayer Perceptron”, Students Conference, ISCON apos:02. IEEE Volume 1, Issue, 16-17, 2002
[11] T. N. Sainath, C. Parada: „Convolutional Neural Networks for Small-footprint Keyword Spotting”, Interspeech, 2015
[12] K. J. Piczak: „Environmental Sound Classification With Convolutional Neural Networks”, IEEE International Workshop on Machine Learning For Signal Processing, 2015
[13] O. Abdel-Hamid, A. Mohamed, H. Jiang, L. Deng, G. Penn, D. Yu: „Convolutional Neural Networks for Speech Recognition”, IEEE/ACM Transactions on audio, speech and language processing, vol. 22, NO. 10, 2014
[14] Tadeusiewicz R.: Sieci neuronowe. Akademicka Oficyna Wydawnicza RM, 1993
[15] Nielsen M.: Neural Networks and Deep Learning. Determination Press, 2015
[16] Goodfellow I., Bengio Y. i Courville A., Deep Learning, 2016
[17] Wprowadzenie do kowolucyjnych sieci neuronowych https://towardsdatascience.com/simple-introduction-to-convolutional-neural-networks-cdf8d3077bac, czerwiec 2019
[18] Strona projektu Tensorflow https://www.tensorflow.org/, czerwiec 2019
[19] Pete Warden: Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition, 2018
[20] Repozytorium biblioteki Tensorflow https://github.com/tensorflow/tensorflow, czerwiec 2019
[21] Dokumentacja biblioteki Seaborn https://seaborn.pydata.org/index.html, czerwiec 2019
[2] A. Sanchis, A. Juan, E. Vidal: „A Word-Based Naive Bayes Classifier for Confidence Estimation in Speech Recognition”, IEEE Transactions on audio, speech and language processing, vol. 20, NO. 2, 2012
[3] N. Smith, M. Gales: „Speech Recognition using SVMs”, Cambridge University Engineering Dept, 2002
[4] C. Ittichaichareon, S. Suksri, T. Yingthawornsuk: „Speech Recognition using MFCC”, International Conference on Computer Graphics, Simulation and Modeling , 2012
[5] W. M. Campbell, J. P. Campbell, D. A. Reynolds, E. Singer, P. A. Torres-Carrasquillo: „Support vector machines for speaker and language recognition”, Computer Speech and Language 20 210–229, 2006
[6] A. Ganapathiraju, J. E. Hamaker, J. Picone: „Applications of Support Vector Machines to speech recognition”, IEEE Transactions on signal processing, vol 52, NO. 8, 2004
[7] K. Al Smadi, I. Trrad, T. Al Smadi: „ Artificial Intelligence for Speech Recognition Based on Neural Networks”, Journal of Signal and Information Processing, 2015, 6, 66-72, 2015
[8] W. Gevaert, G. Tsenov, V. Mladenov: „Neural networks used for speech recognition”,Journal of automatic control, University of Belgrade, vol. 20:1-7 , 2010
[9] M. Tunckanat, R. Kurban S. Sagiroglu: „Voice Recognition Based On Neural Networks”, IJCI Proceedings of International Conference on Signal Processing, ISSN 1304-2386, Volume:1, Number:2, 2003
[10] A. Ahad, A. Fayyaz, T. Mehmood: „Speech Recognition using Multilayer Perceptron”, Students Conference, ISCON apos:02. IEEE Volume 1, Issue, 16-17, 2002
[11] T. N. Sainath, C. Parada: „Convolutional Neural Networks for Small-footprint Keyword Spotting”, Interspeech, 2015
[12] K. J. Piczak: „Environmental Sound Classification With Convolutional Neural Networks”, IEEE International Workshop on Machine Learning For Signal Processing, 2015
[13] O. Abdel-Hamid, A. Mohamed, H. Jiang, L. Deng, G. Penn, D. Yu: „Convolutional Neural Networks for Speech Recognition”, IEEE/ACM Transactions on audio, speech and language processing, vol. 22, NO. 10, 2014
[14] Tadeusiewicz R.: Sieci neuronowe. Akademicka Oficyna Wydawnicza RM, 1993
[15] Nielsen M.: Neural Networks and Deep Learning. Determination Press, 2015
[16] Goodfellow I., Bengio Y. i Courville A., Deep Learning, 2016
[17] Wprowadzenie do kowolucyjnych sieci neuronowych https://towardsdatascience.com/simple-introduction-to-convolutional-neural-networks-cdf8d3077bac, czerwiec 2019
[18] Strona projektu Tensorflow https://www.tensorflow.org/, czerwiec 2019
[19] Pete Warden: Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition, 2018
[20] Repozytorium biblioteki Tensorflow https://github.com/tensorflow/tensorflow, czerwiec 2019
[21] Dokumentacja biblioteki Seaborn https://seaborn.pydata.org/index.html, czerwiec 2019
Article Details
Basiakowski, J. (2019). Applying of machine learning in the construction of a voice-controlled interface on the example of a music player . Journal of Computer Sciences Institute, 13, 302–309. https://doi.org/10.35784/jcsi.1324
Abstract views: 335
License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
