This paper describes a new database of binaural room impulse responses (BRIR), referred to as the Aachen Impulse Response (AIR) database. The main field of application of this database is the evaluation of speech enhancement algorithms dealing with room reverberation. The measurements with a dummy head took place in a low-reverberant studio booth, an office room, a meeting room and a lecture room. Due to the different dimensions and acoustic properties, it covers a wide range of situations where digital hearing aids or other hands-free devices can be used. Besides the description of the database, a motivation for using binaural instead of monaural measurements is given. Furthermore an example using a coherencebased dereverberation technique is provided to show the advantage of this database for algorithm evaluation. The AIR database is being made available online.

The ability of the human auditory system for sound localization mainly depends on the binaural cues, especially interaural time and level differences (ITD and ILD). In the context of digital hearing aids and binaural audio transmission systems, these cues can be severely degraded by independent bilateral signal processing such as dereverberation or noise reduction. This contribution presents a novel two-stage binaural dereverberation algorithm which explicitly preserves the binaural cues. The first stage is based on a statistical model of the room impulse responses (RIR) and comprises a spectral subtraction rule which reduces late reverberation only. It includes a smoothing process of the spectral gains to reduce musical tones. In a second stage, the residual reverberation is attenuated by a dual-channel Wiener filter. This is derived from a coherence model of the reverberant sound field taking into account shadowing effects of the head. The overall binaural-input binaural-output structure efficiently reduces both early and late reverberation. In experiments as well as informal listening tests using measured binaural room impulse responses, the proposed algorithm significantly improves speech quality according to objective and subjective measures. His research interests cover the areas of single-and multichannel speech enhancement algorithms including noise suppression and dereverberation. MagnusSchäfer received the Dipl.-Ing. degree in information and communication technology from RWTH Aachen University, Aachen, Germany, in 2006. He is currently pursuing the Ph.D. degree at the Institute of Communication Systems and Data Processing, RWTH Aachen University. His research interests cover the areas of singleand multichannel speech and audio coding as well as speech enhancement. Thomas Esch (S'07) received the Dipl.-Ing. degree in information and communication technology from

Instrumental evaluation of the perceived audio signal quality is an important tool for the development of audio signal enhancement and transmission systems. There are various single channel measures which can be used for different application scenarios. Binaural signals have not received much focus so far and no sophisticated model of spatial perception is utilized in the available measures. In this contribution, an extension to Perceptual Evaluation of Audio Quality (PEAQ) is presented which makes use of a recently proposed binaural hearing model. It is shown that the inclusion of spatial information into the instrumental quality measurement leads to a strongly increased correlation between the instrumental measure and a listening test.

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