The Sound Character Space of Spectrally Distorted Telephone Speech and Its Impact on Quality

Möller S, Raake A, Wältermann M. The Sound Character Space of Spectrally Distorted Telephone Speech and Its Impact on Quality. In: AES Convention 124. Audio Engineering Society; 2008. Paper 7464. Available from: https://aes.org/publications/elibrary-page/?id=14594

@inproceedings{Moller2008_14594,
  author = {Möller, Sebastian and Raake, Alexander and Wältermann, Marcel},
  title = {{The Sound Character Space of Spectrally Distorted Telephone Speech and Its Impact on Quality}},
  booktitle = {AES Convention 124},
  note = {Paper 7464},
  year = {2008},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=14594}
}

TY  - CPAPER
TI  - The Sound Character Space of Spectrally Distorted Telephone Speech and Its Impact on Quality
AU  - Möller, Sebastian
AU  - Raake, Alexander
AU  - Wältermann, Marcel
T2  - AES Convention 124
M1  - Paper 7464
PY  - 2008
DA  - 2008/05/06
UR  - https://aes.org/publications/elibrary-page/?id=14594
PB  - Audio Engineering Society
LA  - en
AB  - Spectral distortions of speech transmitted over a telephone channel may stem from linear channel filtering, codecs, electro-acoustic properties of end-user terminals, or the acoustic environment at send side. In this contribution, a study is presented which aims at revealing the perceptual space of spectrally distorted telephone speech and establishing a link to the overall quality of the speech. Two dimensions were identified as relevant for explaining the perceived quality: "Indirectness" and "brightness". Whereas "brightness" is related to the center frequency of a transfer function, "indirectness" is correlated with the equivalent rectangular bandwidth and constitutes the dominating factor in the perceptual space in terms of covered variance. The concept of the bandwidth impairment factor which fits into the framework of the so-called E-Model and which is based on these simple parameters for computing the integral quality of spectrally distorted speech could successfully be applied to the given data.
ER  -