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Speech Quality Fundamentals

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Human Information Processing in Speech Quality Assessment

Part of the book series: T-Labs Series in Telecommunication Services ((TLABS))

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Abstract

This chapter defines important concept pairs such as quality of experience versus quality of service, quality element versus quality feature, and perceived quality versus judged quality, that will be used throughout the present book. Moreover, two approaches are introduced for modeling speech quality perception either on the psychophysical or functional (psychological/psychophysiological) level of explanation.

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Notes

  1. 1.

    A similar notion of “micro-valence” or perceived valence is discussed by Lebrecht and colleagues [25]: “Everyday objects automatically evoke some perception of valence[, which] can be considered a higher-level object property that connects vision [and audition] to behavior […]. Thus, valence is not a label or judgment applied to the object postrecognition, but rather an integral component of mental object representations” (p. 1). In contrast, affective valence would only be associated with fully fledged, high-arousal emotional and motivational states or, e.g., with startle responses triggered by more intense stimulatory change. Either valence dimension describes a continuum from “negative/bad” or “unpleasant” to “positive/good” or “pleasant” [24], characterizing the evaluative percept (perceived valence) or affective experience (affective valence).

  2. 2.

    The vector model actually presents a special case of an ideal point model, as elaborated in [23].

  3. 3.

    Again, the “quality event” (or “quality” in general; see Fig. 2.4) is clearly associated with an outcome of higher-cognitive processing, namely, the quality judgment. In the terminology developed in Sect. 2.1.2.2, this way of experiencing quality would be equivalent to “judged quality.”

References

  1. ISO 9000:2005, Quality Management Systems – Fundamentals and Vocabulary (International Organization for Standardization (ISO), Geneva, 2005)

    Google Scholar 

  2. ISO 8402:1994, Quality Management and Quality Assurance – Vocabulary (International Organization for Standardization (ISO), Geneva, 1994)

    Google Scholar 

  3. ITU-T Recommendation P.10/G.100, Vocabulary for Performance, Quality of Service and Quality of Experience (International Telecommunication Union (ITU), Geneva, 2017)

    Google Scholar 

  4. M. Varela, L. Skorin-Kapov, T. Ebrahimi, Quality of service versus quality of experience, in Quality of Experience, ed. by S. Möller, A. Raake (Springer, Cham, 2014), pp. 85–96

    Chapter  Google Scholar 

  5. A. Raake, Speech Quality of VoIP: Assessment and Prediction (John Wiley & Sons, Ltd, Chichester, 2006)

    Book  Google Scholar 

  6. A. Raake, S. Egger, Quality and quality of experience, in Quality of Experience, ed. by S. Möller, A. Raake (Springer, Cham, 2014), pp. 11–33

    Chapter  Google Scholar 

  7. S. Bech, N. Zacharov, Perceptual Audio Evaluation – Theory, Method and Application (John Wiley & Sons, Ltd, Chichester, 2006)

    Book  Google Scholar 

  8. M. Schoeffler, A. Silzle, J. Herre, Evaluation of spatial/3D audio: basic audio quality versus quality of experience. IEEE J. Sel. Top. Sign. Proces. 11(1), 75–88 (2017)

    Article  Google Scholar 

  9. P. Le Callet, S. Möller, A. Perkis (eds.), Qualinet White Paper on Definitions of Quality of Experience, European Network on Quality of Experience in Multimedia Systems and Services (COST Action IC 1003), Version 1.2 (2013)

    Google Scholar 

  10. U. Reiter, K. Brunnström, K. De Moor, M.-C. Larabi, M. Pereira, A. Pinheiro, J. You, A. Zgank, Factors influencing quality of experience, in Quality of Experience, ed. by S. Möller, A. Raake (Springer, Cham, 2014), pp. 55–72

    Chapter  Google Scholar 

  11. U. Engelke, H. Kaprykowsky, H.-J. Zepernick, P. Ndjiki-Nya, Visual attention in quality assessment. IEEE Signal Process. Mag. 28(6), 50–59 (2011)

    Article  Google Scholar 

  12. U. Engelke, D.P. Darcy, G.H. Mulliken, S. Bosse, M.G. Martini, S. Arndt, J.-N. Antons, K.Y. Chan, N. Ramzan, K. Brunnström, Psychophysiology-based QoE assessment: a survey. IEEE J. Sel. Top. Sign. Proces. 11(1), 6–21 (2017)

    Article  Google Scholar 

  13. S. Uhrig, G. Mittag, S. Möller, J.-N. Voigt-Antons, P300 indicates context-dependent change in speech quality beyond phonological change. J. Neural Eng. 16(6), 066008 (2019)

    Google Scholar 

  14. E.M. Kaya, M. Elhilali, Investigating bottom-up auditory attention. Front. Hum. Neurosci. 8 (2014)

    Google Scholar 

  15. A. Raake, Does the content of speech influence its perceived sound quality? Sign 1, 1170–1176 (2002)

    Google Scholar 

  16. S. Möller, Quality Engineering: Qualität kommunikationstechnischer Systeme (Springer, Heidelberg, 2010)

    Book  Google Scholar 

  17. M. Maguire, Context of use within usability activities. Int. J. Hum. Comput. Stud. 55(4), 453–483 (2001)

    Article  Google Scholar 

  18. T. Hoßfeld, P.E. Heegaard, M. Varela, S. Möller, QoE beyond the MOS: an in-depth look at QoE via better metrics and their relation to MOS. Qual. User Exp. 1(1), 2 (2016)

    Google Scholar 

  19. U. Jekosch, Voice and Speech Quality Perception: Assessment and Evaluation. Signals and Communication Technology (Springer, Berlin, 2005)

    Google Scholar 

  20. S. Möller, Assessment and Prediction of Speech Quality in Telecommunications (Springer US, Boston, 2000)

    Book  Google Scholar 

  21. S. Möller, Quality of transmitted speech for humans and machines, in Communication Acoustics, ed. by J. Blauert (Springer, Heidelberg, 2005), pp. 163–192

    Chapter  Google Scholar 

  22. M. Wältermann, A. Raake, S. Möller, Quality dimensions of narrowband and wideband speech transmission. Acta Acust. United Acust. 96(6), 1090–1103 (2010)

    Article  Google Scholar 

  23. M. Wältermann, Dimension-Based Quality Modeling of Transmitted Speech. T-Labs Series in Telecommunication Services (Springer, Heidelberg, 2013)

    Google Scholar 

  24. M.M. Bradley, P.J. Lang, Emotion and Motivation, ed by J.T. Cacioppo, L.G. Tassinary, G. Berntson (Cambridge University Press, Cambridge, 2007), pp. 581–607

    Google Scholar 

  25. S. Lebrecht, M. Bar, L.F. Barrett, M.J. Tarr, Micro-valences: perceiving affective valence in everyday objects. Front. Psychol. 3 (2012)

    Google Scholar 

  26. F. Rumsey, Spatial quality evaluation for reproduced sound: terminology, meaning, and a scene-based paradigm. J. Audio Eng. Soc. 50(9), 651–666 (2002)

    Google Scholar 

  27. S. Uhrig, G. Mittag, S. Möller, J.-N. Voigt-Antons, Neural correlates of speech quality dimensions analyzed using electroencephalography (EEG). J. Neural Eng. 16(3), 036009 (2019)

    Google Scholar 

  28. J. Blauert, U. Jekosch, A layer model of sound quality, in Proceedings of the 3rd International Workshop on Perceptual Quality of Systems (PQS 2010) (2010), pp. 18–23

    Google Scholar 

  29. J. Blauert, U. Jekosch, Auditory quality of performance spaces for music – the problem of the references, in Proceedings of the 19th International Congress on Acoustics (ICA 2007) (2007), pp. 1205–1210

    Google Scholar 

  30. U. Jekosch, Assigning meaning to sounds – semiotics in the context of product-sound design, in Communication Acoustics, ed. by J. Blauert (Springer, Heidelberg, 2005), pp. 193–221

    Chapter  Google Scholar 

  31. M. Barreda-Ángeles, R. Pépion, E. Bosc, P. Le Callet, A. Pereda-Baños, Exploring the effects of 3D visual discomfort on viewers’ emotions, in 2014 IEEE International Conference on Image Processing (ICIP) (IEEE, Paris, 2014), pp. 753–757

    Google Scholar 

  32. S. Uhrig, S. Möller, D.M. Behne, U.P. Svensson, A. Perkis, Testing a quality of experience (QoE) model of loudspeaker-based spatial speech reproduction, in 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX) (IEEE, Athlone, 2020), pp. 1–6

    Google Scholar 

  33. J.T. Cacioppo, S.L. Crites, W.L. Gardner, G.G. Berntson, Bioelectrical echoes from evaluative categorizations: I. A late positive brain potential that varies as a function of trait negativity and extremity. J. Pers. Soc. Psychol. 67(1), 115–125 (1994)

    Google Scholar 

  34. ITU-R Recommendation BS.1284-2, General Methods for the Subjective Assessment of Sound Quality (International Telecommunication Union (ITU), Geneva, 2019)

    Google Scholar 

  35. R. Nicol, L. Gros, C. Colomes, M. Noisternig, O. Warusfel, H. Bahu, B.F.G. Katz, A roadmap for assessing the quality of experience of 3D audio binaural rendering, in EAA Joint Symposium on Auralization and Ambisonics, Berlin (2014), pp. 100–106

    Google Scholar 

  36. ITU-R Recommendation BS.1116-3, Methods for the Subjective Assessment of Small Impairments in Audio Systems (International Telecommunication Union (ITU), Geneva, 2015)

    Google Scholar 

  37. ITU-T Recommendation G.107, The E-model: A Computational Model for Use in Transmission Planning (International Telecommunication Union (ITU), Geneva, 2015)

    Google Scholar 

  38. J. Skowronek, A. Raake, Assessment of cognitive load, speech communication quality and quality of experience for spatial and non-spatial audio conferencing calls. Speech Commun. 66, 154–175 (2015)

    Article  Google Scholar 

  39. S. Möller, W.-Y. Chan, N. Côté, T. Falk, A. Raake, M. Wältermann, Speech quality estimation: models and trends. IEEE Signal Process. Mag. 28(6), 18–28 (2011)

    Article  Google Scholar 

  40. E. Datteri, F. Laudisa, Box-and-arrow explanations need not be more abstract than neuroscientific mechanism descriptions. Front. Psychol. 5 (2014)

    Google Scholar 

  41. G.G. Berntson, J.T. Cacioppo, Reductionism, in Paradigms in Theory Construction, ed. by L. L’Abate (Springer, New York, 2012), pp. 365–374

    Chapter  Google Scholar 

  42. S. Möller, R. Heusdens, Objective estimation of speech quality for communication systems. Proc. IEEE 101(9), 1955–1967 (2013)

    Article  Google Scholar 

  43. S. Möller, M. Wältermann, M.-N. Garcia, Features of quality of experience, in Quality of Experience, ed. by S. Möller, A. Raake (Springer, Cham, 2014), pp. 73–84

    Chapter  Google Scholar 

  44. B.J. McDermott, Multidimensional analyses of circuit quality judgments. J. Acoust. Soc. Am. 45(3), 774–781 (1969)

    Article  Google Scholar 

  45. M. Wältermann, A. Raake, S. Möller, The sound character space of spectrally distorted telephone speech and its impact on quality, in Audio Engineering Society Convention 124 (2008)

    Google Scholar 

  46. M. Wältermann, A. Raake, S. Möller, Modeling of integral quality based on perceptual dimensions – a framework for a new instrumental speech-quality measure, in ITG Conference on Voice Communication [8. ITG-Fachtagung] (2008), pp. 1–4

    Google Scholar 

  47. N. Côté, Integral and Diagnostic Intrusive Prediction of Speech Quality, ser. T-Labs Series in Telecommunication Services (Springer, Heidelberg, 2011)

    Google Scholar 

  48. A. Raake, J. Blauert, Comprehensive modeling of the formation process of sound-quality, in 2013 Fifth International Workshop on Quality of Multimedia Experience (QoMEX) (IEEE, Klagenfurt am Wörthersee, 2013), pp. 76–81

    Google Scholar 

  49. A.S. Bregman, Auditory Scene Analysis: The Perceptual Organization of Sound (MIT Press, Cambridge, 1990)

    Book  Google Scholar 

  50. B.C.J. Moore, An Introduction to the Psychology of Hearing, 6th edn. (Brill, Leiden, 2013)

    Google Scholar 

  51. J. Skowronek, A. Raake, Conceptual model of multiparty conferencing and telemeeting quality, in 2015 Seventh International Workshop on Quality of Multimedia Experience (QoMEX) (2015), pp. 1–6

    Google Scholar 

  52. J.-N. Antons, Neural Correlates of Quality Perception for Complex Speech Signals. T-Labs Series in Telecommunication Services (Springer, Cham, 2015)

    Google Scholar 

  53. S. Arndt, Neural Correlates of Quality During Perception of Audiovisual Stimuli. T-Labs Series in Telecommunication Services (Springer, Singapore, 2016)

    Google Scholar 

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  1. Quality and Usability Lab, Technische Universität Berlin, Berlin, Germany

    Stefan Uhrig

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Uhrig, S. (2022). Speech Quality Fundamentals. In: Human Information Processing in Speech Quality Assessment. T-Labs Series in Telecommunication Services. Springer, Cham. https://doi.org/10.1007/978-3-030-71389-8_2

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  • DOI: https://doi.org/10.1007/978-3-030-71389-8_2

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