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Tytuł artykułu

Enhancing speech signals based on an mems microphone array and temporal differences in the incoming signal

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The development of the Internet of things and automatisation in everyday life also influences our houses. There are more and more devices on the market which can be controlled remotely. One kind of such control involves the use of voice signals. This method tends to use microphone arrays and dedicated algorithms to enhance the speech signal and recognize the words in it. In this project, a small 5-microphone array was developed. To enhance the quality of the signal, dedicated software was written. It consists of several modules, including the direction of arrival estimation, denoising, and differentiation between adults and children. The results showed that the custom algorithm can increase the signal to noise ratio by up to 6 dB.
Rocznik
Strony
art. no. 2022202
Opis fizyczny
Bibliogr. 19 poz., fot. kolor., 1 rys., wykr.
Twórcy
autor
  • Department of Acoustics, Faculty of Physics, Adam Mickiewicz University,
  • LARS Andrzej Szymański, Niepruszewo
Bibliografia
  • 1. M.H. Jabardi; Voice controlled Smart Electric-Powered wheelchair based on Artificial Neural Network; International Journal of Advanced Research in Computer Science 2017, 8(5), 31-37. DOI: 10.26483/IJARCS.V8I5.3650
  • 2. M.Y.A. Khan, H. Rasheed, U. Shahid; Voice Controlled Robot using Neural Network based Speech Recognition using Linear Predictive Coding; Bahria University Journal of Information & Communica-tion Technology 2016, 9, 47-49.
  • 3. A. Brenon, F. Portet, M. Vacher; Arcades: A deep model for adaptive decision making in voice controlled smart-home; Pervasive and Mobile Computing 2018, 49, 92-110. DOI: 10.1016/j.pmcj.2018.06.011
  • 4. A. Chandini, P.V. Bhaskar Reddy; Smart home automation using a voice-bot; International Journal of Advanced Research in Computer Science 2020, 11, 194-200. DOI: 10.26483/IJARCS.V11I0.6584
  • 5. B. Busatlic, N. Dogru, I. Lera, E. Sukic; Smart homes with voice activated systems for disabled people; TEM Journal 2017, 6(1), 103-107. DOI: 10.18421/TEM61-15
  • 6. K. O’Brien, A. Liggett, V. Ramirez‐Zohfeld, P. Sunkara, L. A. Lindquist; Voice‐Controlled Intelligent Personal Assistants to Support Aging in Place; J. Am. Geriatr. Soc. 2020, 68(1), 176-179. DOI: 10.1111/jgs.16217
  • 7. G.W. Elko, J. Meyer; Microphone Arrays; In: Springer Handbook of Speech Processing; M. Brandstein, D. Ward, Eds.; Springer: Berlin, Heidelberg, 2008, 1021-1041.
  • 8. D.P. Jarrett, E.A.P. Habets, P.A. Naylor; Theory and Applications of Spherical Microphone Array Processing; Springer: Cham, 2017.
  • 9. J. Benesty, J. Chen; Study and Design of Differential Microphone Arrays; Springer: Berlin, 2013.
  • 10. J. Chen, J. Benesty; Design and Implementation of Small Microphone Arrays for Acoustic and Speech Signal Processing, http://www.iwaenc2014.org/files/2014_IWAENC_MicrophoneArrays_Chen.pdf (Accessed: March 16, 2018).
  • 11. S. Dodo, M. Moonen; Superdirective beamforming robust against microphone mismatch; In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Toulouse, France, May 14-19, 2006; IEEE: Piscataway, USA, 2006, Vol. 5.
  • 12. G. Huang, J. Benesty, J. Chen; Subspace superdirective beamforming with uniform circular microphone arrays; Proceedings of 2016 International Workshop on Acoustic Signal Enhancement (IWAENC); Xi’an, China, September 13-16, 2016; IEEE: Piscataway, USA, 2016.
  • 13. B. van den Broeck, A. Bertrand, P. Karsmakers, B. Vanrumste, H. van Hamme, M. Moonen; Time-domain GCC-phat sound source localization for small microphone arrays; Proceedings of 5th European DSP Education and Research Conference (EDERC); Amsterdam, Netherlands, September 13-14, 2012; IEEE: Piscataway, USA, 2012, 76-80. DOI: 10.1109/EDERC.2012.6532229
  • 14. A. Kuklasinski; Multi-channel dereverberation for speech intelligibility improvement in hearing aid applications; Ph.D. Thesis, Aalborg University, Aalborg, Denmark, 2016.
  • 15. L. Hernández Acosta, D. Reinhardt; A survey on privacy issues and solutions for Voice-controlled Digital Assistants; Pervasive and Mobile Computing 2022, 80, 101523. DOI: 10.1016/j.pmcj.2021.101523
  • 16. R. Hasan, R. Shams, M. Rahman; Consumer trust and perceived risk for voice-controlled artificial intelligence: The case of Siri; Journal of Business Research 2021, 131, 591-597. DOI: 10.1016/j.jbusres.2020.12.012
  • 17. E. Sarradj, G. Herold; A Python framework for microphone array data processing; Applied Acoustics 2017, 116, 50-58. DOI: 10.1016/J.APACOUST.2016.09.015
  • 18. M. Berouti, R. Schwartz, J. Makhoul; Enhancement of speech corrupted by acoustic noise; In: ICASSP’79. IEEE International Conference on Acoustics, Speech, and Signal Processing; Washington, USA, April 2-4, 1979; IEEE: Piscataway, USA, 1979, 208-211. DOI: 10.1109/icassp.1979.1170788
  • 19. J. Grythe; Array gain and reduction of self-noise; Norsonic, Technical note, Oslo, 2016.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-20fabcd7-3355-42e2-8cf5-7a4d63c899c2
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