Bar-Ilan University

About: Bar-Ilan University is a education organization based out in Ramat Gan, Israel. It is known for research contribution in the topics: Population & Poison control. The organization has 12835 authors who have published 34964 publications receiving 995648 citations. The organization is also known as: Bar Ilan University & BIU.

Collective Rent Dissipation

Abstract: The theory of rent seeking was initiated by Tullock (1967, 1980), followed by Krueger (1974) and Posner (1975) and, more recently, extended in various directions by Allard (1988); Appelbaum and Katz (1986a, b, c); Gradstein and Nitzan (1989); Hillman and Katz (1984, 1987), Hillman and Samet (1987); Hillman and Riley (1989); Katz et al. (1990); Long and Vousden (1987); Ursprung (1990) and Varian (1989). The purpose of this paper is to extend this theory by introducing the possibility of collective-group rent seeking with voluntary individual decisions regarding their extent of participation in the collective rent-seeking efforts.

A summary of the REVERB challenge: state-of-the-art and remaining challenges in reverberant speech processing research

Abstract: In recent years, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multichannel dereverberation techniques and automatic speech recognition (ASR) techniques that are robust to reverberation. In this paper, we describe the REVERB challenge, which is an evaluation campaign that was designed to evaluate such speech enhancement (SE) and ASR techniques to reveal the state-of-the-art techniques and obtain new insights regarding potential future research directions. Even though most existing benchmark tasks and challenges for distant speech processing focus on the noise robustness issue and sometimes only on a single-channel scenario, a particular novelty of the REVERB challenge is that it is carefully designed to test robustness against reverberation, based on both real, single-channel, and multichannel recordings. This challenge attracted 27 papers, which represent 25 systems specifically designed for SE purposes and 49 systems specifically designed for ASR purposes. This paper describes the problems dealt within the challenge, provides an overview of the submitted systems, and scrutinizes them to clarify what current processing strategies appear effective in reverberant speech processing.