Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node's measurement and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighboring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly encoding multiple sources. We focus on the case where node measurements are in form of noisy linearly mixed combinations of the sources and the acoustic channel mixing matrices are invertible. For this problem, we derive the rate-distortion function for vector Gaussian sources and under covariance distortion constraints.Comment: 10 pages, to be presented at the IEEE DCC'1

Distributed Remote Vector Gaussian Source Coding with Covariance Distortion Constraints

In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the optimal rate for encoding the observations subject to a covariance matrix distortion constraint and in the presence of side information at the decoder. For this problem, we derive lower and upper bounds on the rate-distortion function (RDF) for the Gaussian case, which in general do not coincide. We then provide some cases, where the RDF can be derived exactly. We also show that previous results on specific instances of this problem can be generalized using our results. We finally show that if the distortion measure is the mean squared error, or if it is replaced by a certain mutual information constraint, the optimal rate can be derived from our main result.Comment: This is the final version accepted at ISIT'1

Method for subjective assessment of immersion in audiovisual experiences

Studying immersion in audiovisual experiences can help technologists deliver engaging and enhanced experiences. As a first step toward this goal this paper details an investigation conducted to establish an experimental paradigm for quantifying immersion and determining the influence of immersive tendency (susceptibility to become immersed) on immersion. A balanced incomplete block design was employed where 21 assessors rated 15 commercially available stimuli (representative of the highest quality encountered in domestic AV applications) without repetitions and simultaneous comparisons. The assessors were instructed to rate immersion on a graphic line scale and document their familiarity with the content. A questionnaire was administered to measure the immersive tendency after the rating experiment. The results show that the assessors can comprehend the description of immersion and follow the experimental protocol. It is found that immersion is a graded experience and the correlation between immersive tendencies and immersion ratings is predominantly statistically insignificant. The experimental paradigm presented in this paper can form the framework for assessing immersion and developing novel methods to thoroughly explore the concept of immersion in audiovisual experiences