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Part of the book series: Mathematics for Industry ((MFI,volume 20))

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Abstract

The basic, perceived attributes of sound can be divided into those qualities that distinguish different sounds independent of location (temporal sensations) and those related to a sound’s perceived location in space (spatial sensations). Temporal sensations include pitch, loudness, timbre, and duration. They can be described in terms of temporal factors extracted from the autocorrelation function (ACF). The ACF has the same information as the power density spectrum of the signal under analysis. From the ACF, however, significant factors may be extracted, which are related to temporal sensations.

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References

  • Ando Y (1998) Architectural acoustics: blending sound sources, sound fields, and listeners. AIP Press, Springer, New York

    Book  Google Scholar 

  • Ando Y, Sato S, Sakai H (1999) Fundamental subjective attributes of sound fields based on the model of auditory brain system. In: Sendra JJ (ed) Computational acoustics in architecture. WIT Press, Southampton, pp 63–99

    Google Scholar 

  • Cariani PA (1999) Temporal coding of periodicity pitch in the auditory system: an overview. Neural Plast 6:147–172

    Article  Google Scholar 

  • Cariani PA (2001) Neural timing nets. Neural Netw 14:737–753

    Article  Google Scholar 

  • Cariani PA, Delgutte B (1996a) Neural correlates of the pitch of complex tones. I. Pitch and pitch salience. J Neurophysiol 76:1698–1716

    Google Scholar 

  • Cariani PA, Delgutte B (1996b) Neural correlates of the pitch of complex tones. II. Pitch shift, pitch ambiguity, phase invariance, pitch circularity, rate pitch, and the dominance region for pitch. J Neurophysiol 76:1717–1734

    Google Scholar 

  • de Cheveigne A (1998) Cancellation model of pitch perception. J Acoust Soc Am 103:1261–1271

    Article  Google Scholar 

  • Dubrovskii NA, Chernyak RI (1969) Binaural loudness summation under varying degrees of noise correlation. Sov Phys Acoust 14:326–332

    Google Scholar 

  • Fraisse P (1984) Perception and estimation of time. Annu Rev Psychol 35:1–36

    Article  Google Scholar 

  • Fujii K, Soeta Y, Ando Y (2001) Acoustical properties of aircraft noise measured by temporal and spatial factors. J Sound Vib 241:69–78

    Article  Google Scholar 

  • Fujii K, Atagi J, Ando Y (2002) Temporal and spatial factors of traffic noise and its annoyance. J Temporal Des Arch Environ 2:33–41

    Google Scholar 

  • Goldstein JL (1973) An optimum processor theory for the central formation of the pitch of complex tones. J Acoust Soc Am 54:1496–1516

    Article  Google Scholar 

  • Greenwood DD (1961a) Auditory masking and the critical band. J Acoust Soc Am 33:484–502

    Article  Google Scholar 

  • Greenwood DD (1961b) Critical bandwidth and the frequency of the basilar membrane. J Acoust Soc Am 33:1344–1356

    Article  Google Scholar 

  • Inoue M, Ando Y, Taguti T (2001) The frequency range applicable to pitch identification based upon the auto-correlation function model. J Sound Vib 241:105–116

    Article  Google Scholar 

  • Katsuki Y, Sumi T, Uchiyama H, Watanabe T (1958) Electric responses of auditory neurons in cat to sound stimulation. J Neurophysiol 21:569–588

    Google Scholar 

  • Kitamura T, Sato S, Shimokura R, Ando Y (2002) Measurement of temporal and spatial factors of a flushing toilet noise in a downstairs bedroom. J Temporal Des Arch Environ 2:13–19

    Google Scholar 

  • Levitt H (1971) Transformed up-down procedures in psychophysics. J Acoust Soc Am 49:467–477

    Article  Google Scholar 

  • Licklider JCR (1951) A duplex theory of pitch perception. Experimenta 7:128–134

    Article  Google Scholar 

  • Lundeen C, Small AM (1984) The influence of temporal cue on the strength of periodicity pitches. J Acoust Soc Am 75:1578–1587

    Article  Google Scholar 

  • Marui A, Martens WL (2005) Timbre of nonlinear distortion effects: Perceptual attributes beyond sharpness? In: Proceedings of the conference on interdisciplinary musicology, Montreal, 2005

    Google Scholar 

  • Mathews MV, Pfafflin SM (1965) Effect of filter type on energy-detection models for auditory signal detection. J Acoust Soc Am 38:1055–1056

    Article  Google Scholar 

  • Meddis R, Hewitt M (1991a) Virtual pitch and phase sensitivity of a computer model of the auditory periphery. I: pitch identification. J Acoust Soc Am 89:2866–2882

    Article  Google Scholar 

  • Meddis R, Hewitt M (1991b) Virtual pitch and phase sensitivity of a computer model of the auditory periphery. II: phase sensitivity. J Acoust Soc Am 89:2883–2894

    Article  Google Scholar 

  • Merthayasa IN, Hemmi H, Ando Y (1994) Loudness of a 1 kHz pure tone and sharply (1080 dB/Oct.) filtered noises centered on its frequency. Mem Grad School Sci Tech Kobe Univ 12A:147–156

    Google Scholar 

  • Moore BCJ, Glasberg BR, Baer T (1997) A model for the prediction of thresholds, loudness, and partial loudness. J Audio Eng Soc 45:224–240

    Google Scholar 

  • Moore BCJ, Vickers D, Baer T, Launer S (1999) Factors affecting the loudness of modulated sounds. J Acoust Soc Am 105:2757–2772

    Article  Google Scholar 

  • Ohgushi K (1978) On the role of spatial and temporal cues in the perception of the pitch of complex tones. J Acoust Soc Am 64:764–771

    Article  Google Scholar 

  • Ohgushi K (1980) Physical and psychological factors governing timbre of complex tones. J Acoust Soc Jpn 36:253–259

    Google Scholar 

  • Pressnitzer D, Patterson RD, Krumbholz K (2001) The lower limit of melodic pitch. J Acoust Soc Am 109:2074–2084

    Article  Google Scholar 

  • Saifuddin K, Matsushima T, Ando Y (2002) Duration sensation when listening to pure tone and complex tone. J Temporal Des Arch Environ 2:42–47

    Google Scholar 

  • Sakai H, Sato S, Prodi N, Pompoli R, Ando Y (2001) Measurement of regional environmental noise by use of a PC-based system. An application to the noise near the airport “G. Marconi” in Bologna. J Sound Vib 241:57–68

    Article  Google Scholar 

  • Sakai H, Hotehama T, Prodi N, Pompoli R, Ando Y (2002) Diagnostic system based on the human auditory-brain model for measuring environmental noise—an application to the railway noise-. J Sound Vib 250:9–21

    Article  Google Scholar 

  • Sato S, Kitamura T, Sakai H, Ando Y (2001) The loudness of “complex noise” in relation to the factors extracted from the autocorrelation function. J Sound Vib 241:97–103

    Article  Google Scholar 

  • Sato S, Kitamura T, Ando Y (2002) Loudness of sharply (2068 dB/Octave) filtered noises in relation to the factors extracted from the autocorrelation function. J Sound Vib 250:47–52

    Article  Google Scholar 

  • Soeta Y, Nakagawa S (2008a) Effect of the repetitive components of a noise on loudness. J Temporal Des Arch Environ 8:1–7

    Google Scholar 

  • Soeta Y, Nakagawa S (2008b) The effect of pitch and pitch strength on an auditory-evoked N1 m. NeuroReport 19:783–787

    Article  Google Scholar 

  • Soeta Y, Maruo T, Ando Y (2004) Annoyance of bandpass filtered noises in relation to the factor extracted from autocorrelation function. J Acoust Soc Am 116:3275–3278

    Article  Google Scholar 

  • Soeta Y, Nakagawa S, Matsuoka K (2005) Effects of the critical band on auditory evoked magnetic fields. NeuroReport 16:1787–1790

    Article  Google Scholar 

  • Soeta Y, Yanai K, Nakagawa S, Kotani K, Horii K (2007) Loudness in relation to iterated rippled noise. J Sound Vib 304:415–419

    Article  Google Scholar 

  • Terhardt E (1974) Pitch, consonance, and harmony. J Acoust Soc Am 55:1061–1069

    Article  Google Scholar 

  • Thurstone LL (1927) A law of comparative judgement. Psychol Rev 34:273–289

    Article  Google Scholar 

  • van Noorden L (1982) Two channel pitch perception. In: Clynes M (ed) Music, mind and brain. Plenum, New York, pp 251–269

    Chapter  Google Scholar 

  • Wightman FL (1973a) Pitch and stimulus fine structure. J Acoust Soc Am 54:397–406

    Article  Google Scholar 

  • Wightman FL (1973b) The pattern-transformation model of pitch. J Acoust Soc Am 54:407–416

    Article  Google Scholar 

  • Yost WA (1996) Pitch strength of iterated rippled noise. J Acoust Soc Am 100:3329–3335

    Article  Google Scholar 

  • Yost WA, Hill R (1979) Models of the pitch and pitch strength of ripple noise. J Acoust Soc Am 66:400–410

    Article  Google Scholar 

  • Yost WA, Hill R, Perez-Falcon T (1978) Pitch and pitch discrimination of broadband signals with rippled power spectra. J Acoust Soc Am 63:1166–1173

    Article  Google Scholar 

  • Yost WA, Patterson R, Sheft S (1996) A time domain description for the pitch strength of iterated rippled noise. J Acoust Soc Am 99:1066–1078

    Article  Google Scholar 

  • Yrttiaho S, Tiitien H, May PJC, Leino S (2008) Cortical sensitivity to periodicity of speech sounds. J Acoust Soc Am 123:2191–2199

    Article  Google Scholar 

  • Zhang C, Zeng FG (1997) Loudness of dynamic stimuli in acoustic and electric hearing. J Acoust Soc Am 102:2925–2934

    Article  Google Scholar 

  • Zwicker E (1961) Subdivision of the audible frequency range into critical bands (Frequenzgruppen). J Acoust Soc Am 33:248

    Google Scholar 

  • Zwicker E, Fastl H (eds) (1999) Psychoacoustics: facts and models. Springer, Berlin

    Google Scholar 

  • Zwicker E, Flottorp G, Stevens SS (1957) Critical bandwidth in loudness summation. J Acoust Soc Am 29:548–557

    Article  Google Scholar 

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Soeta, Y., Ando, Y. (2015). Temporal Primary Sensations of Noise. In: Neurally Based Measurement and Evaluation of Environmental Noise. Mathematics for Industry, vol 20. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55432-5_4

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  • DOI: https://doi.org/10.1007/978-4-431-55432-5_4

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