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Effect of highpass filtering on the speech transmission index

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Języki publikacji
EN
Abstrakty
EN
Highpass filters are commonly used in the signal chain of public address systems. One of the reasons for using a highpass filter is to protect the loudspeaker from unwanted low-frequency signals. In addition, it can increase the intelligibility of speech. In this paper, the effect of the cutoff frequency and order of a highpass filter on the speech transmission index, the crest factor, and the sound level are presented. Analyses were performed for an ideal transmission channel, taking into account reverberation time, interfering noise, and high levels of sound. A computer model of the public address system developed by the author, based on the direct STIPA method, was used. This model enables analyses in the nonlinear range of power amplifier operation, which is often used in public address systems but is not considered in commercially available simulation programs.
Rocznik
Strony
art. no. 2022306
Opis fizyczny
Bibliogr. 21 poz., 1 rys., wykr.
Twórcy
  • Wrocław University of Science and Technology, Department of Acoustics, Multimedia and Signal Processing, wyb. Stanisława Wyspiańskiego 27, 50-370 Wrocław
Bibliografia
  • 1. J.C.R. Licklider, I. Pollack; Effects of differentiation, integration, and infinite peak clipping upon the intelligibility of speech; The Journal of the Acoustical Society of America 1948, 20(1), 42-51. DOI: 10.1121/1.1906346
  • 2. I. Pollack; Effects of High Pass and Low Pass Filtering on the Intelligibility of Speech in Noise; The Journal of the Acoustical Society of America 1948, 20(1), 259-266. DOI: 10.1121/1.1906369
  • 3. I. Pollack, J.M. Pickett; Effect of Noise and Filtering on Speech Intelligibility at High Levels; The Journal of the Acoustical Society of America 1957, 29(2), 1328-1329. DOI: 10.1121/1.1908784
  • 4. I.B. Thomas, R.J. Niederjohn; The Intelligibility of Filtered-Clipped Speech in Noise; J. Audio Eng. Soc. 1970, 18 (3), 299-303.
  • 5. I.B. Thomas, W.J. Ohley; Intelligibility enhancement through spectral weighting; Proceedings of the 1972 IEEE Conference on Speech Communication and Processing, Boston, USA, 1972, 360-363.
  • 6. R.J. Niederjohn, J.H. Grotelueschen; The enhancement of speech intelligibility in high noise levels by high-pass filtering followed by rapid amplitude compression; IEEE Trans. Acous. Speech and Sig. Proc. 1976, 24(4), 277-282. DOI: 10.1109/TASSP.1976.1162824
  • 7. S. Brachmański; Effect of additive interference on speech transmission; Archives of Acoustics 2002, 27(2), 95-108.
  • 8. S. Brachmański; Selected issues of quality assessment of speech signal transmission (in Polish); Oficyna Wydawnicza Politechniki Wrocławskiej: Wrocław, Poland, 2015.
  • 9. A.R. Thornton, P.J. Abbas.; Low-frequency hearing loss: Perception of filtered speech, psychophysical tuning curves, and masking; The Journal of the Acoustical Society of America 1980, 67(2), 638-643.
  • 10. J. N. Saba, J. H. L. Hansen; The effects of Lombard perturbation on speech intelligibility in noise for normal hearing and cochlear implant listeners; The Journal of the Acoustical Society of America 2022, 151(2) :1007. DOI: 10.1121/10.0009377
  • 11. IEC 60268-16:2020, Sound system equipment - Part 16: Objective rating of speech intelligibility by speech transmission index.
  • 12. T. Houtgast, H.J.M. Steeneken; The Modulation Transfer Function in rooms acoustics as a predictor of speech intelligibility; The Journal of the Acoustical Society of America 1973, 54(2), 557-557. DOI: 10.1121/1.1913632
  • 13. T. Houtgast, H.J.M. Steeneken; R. Plomp; Predicting speech intelligibility in rooms from the modulation transfer function. I. General room acoustics; Acta Acustica united with Acustica 1980, 46(1), 60-72.
  • 14. H.J.M. Steeneken, T. Houtgast; Mutual dependence of the octave-band weights in predicting speech intelligibility; Speech Communication 1999, 28, 109- 123.
  • 15. P. Dziechciński; Effect of Power Amplifier Distortion on the Speech Transmission Index for Public Address Systems; Archives of Acoustics 2022, 47(2), 191-199. DOI: 10.24425/aoa.2022.141649
  • 16. B. B. Monson, J. Caravello; The maximum audible low-pass cutoff frequency for speech; The Journal of the Acoustical Society of America 2019, 146. DOI: 10.1121/1.5140032
  • 17. K. S. Pearson, R. L. Bennett, S. A. Fidell; Speech Levels in Various Noise Environments, Office of Health and Ecological Effects; Office of Research and Development US EPA: Washington, 1977.
  • 18. P. Dziechcinski; A computer model for calculating the speech transmission index using the direct STIPA method; Vibrations in Physical Systems 2019, 30(1), 2019129-1 - 2019129-8.
  • 19. C. Rapp; Effects of HPA-nonlinearity on a 4-DPSK/OFDM-signal for a digital sound broadcasting system; Proceedings of 2nd European Conference on Satellite Communications, Liege, Belgium, 1991, 179-184.
  • 20. CEN/TS 54-32; Fire detection and fire alarm systems. Planning, design, installation, commissioning, use and maintenance of voice alarm systems; 2015.
  • 21. Recommendation ITU-R BS.1770-4; Algorithms to measure audio programme loudness and true-peak audio level; 2015.
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-d3bfd101-6a7b-4baa-9bfb-4278be2f1561
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