Dr Sunish George

IoSR

Qualifications: B.Tech (EE), M.Tech (DEAC)

Email:

Further information

Biography

Sunish George started his PhD at Institute of Sound Recording in April 2005 and graduated successfully in July 2009. He is now working at Fraunhofer-Institut für Integrierte Schaltungen IIS. Previously, he graduated in Electronic Engineering from Cochin University of Science and Technology, Kochi, Kerala, India; and was awarded the Masters degree in Digital Electronics and Advanced Communication from Manipal Academy of Higher Education, Manipal, Karnataka, India.

Publications

  • Sunish George (2009). Objective models for predicting selected multichannel audio quality attributes". PhD Thesis, Institute of Sound Recording, University of Surrey.
  • George, S., Zielinski, S., Rumsey, F., Conetta, R., Dewhirst, M., Jackson, P.J.B., Meares, D. & Bech, S. (2008). "An Unintrusive Objective Model for Predicting the Sensation of Envelopment Arising from Surround Sound Recordings". Proceedings of the Audio Engineering Society 125th Convention, Oct 2-5, San Francisco, USA, Preprint 7599.
  • George, S., Zielinski, S., Rumsey, F. & Bech, S. (2008). "Evaluating the sensation of envelopment arising from 5-channel surround sound recordings". Proceedings of the Audio Engineering Society 124th Convention, May 17-20, Amsterdam, Preprint 7382.
  • Sunish George, Slawomir Zielinski, Francis Rumsey: "Feature Extraction for the Prediction of Multichannel Spatial Audio Fidelity", IEEE Transcations on Audio, Speech, and Language Processing, Vol. 14, No. 6, pp. 1994-2005 (November, 2006).
  • Sunish George, Slawomir Zielinski, Francis Rumsey: "Initial developments of an objective method for the prediction of basic audio quality for surround audio recordings", presented at 120th AES convention at Paris, 20-23 May 2006.
  • Sunish George, Slawomir Zielinski, Francis Rumsey: "Prediction of Basic Audio Quality for multichannel audio recordings: Initial developments", DMRN Workshop, London, December 2005

Research Project

Perceptual meter for multichannel audio quality

Sunish George
Slawek Zielinski
Francis Rumsey

This project worked towards the development of a generic model that predicts multichannel audio quality. Existing objective models that predict audio quality were evaluated and it was concluded that most objective models that exist today are not capable of predicting multichannel audio quality in their current form. Therefore, important multichannel audio quality attributes were identified and an attempt was made to predict some of them using features derived from the recordings themselves.

The project was completed in two phases. The selected attributes in the first phase were basic audio quality, timbral fidelity, frontal spatial fidelity and surround spatial fidelity since they were the most frequently reported. Envelopment was selected in the second phase since it was reported as an important attribute of multichannel audio in several elicitation experiments. The listening tests in the first phase were conducted according to ITU-R BS 1534-1 recommendation. A novel test paradigm was employed for evaluating envelopment.

The models were calibrated by employing regression analysis techniques. The models in the first phase were of double-ended type and features IACC measurements, spectral centroid, spectral rolloff and centroid of coherence were proved to be useful for the predictions. The model for predicting envelopment was of single-ended type and features IACC measurements, spectral rolloff, area of sound distribution, inter-channel coherence and extent of coverage angle was proved to be important for prediction.

The calibrated models were validated using the scores obtained from independent listening tests. The predicted scores from validation experiments showed high correlation with the actual scores and the accuracy of the models were comparable to the inter-listener errors encountered in typical listening tests. The developed models could either be used as independent applications or act as building blocks of a generic model that predicts multichannel audio quality.