Magnus Schäfer

A binaural room impulse response database for the evaluation of dereverberation algorithms

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 coherence-based dereverberation technique is provided to show the advantage of this database for algorithm evaluation. The AIR database is being made available online.

Model-Based Dereverberation Preserving Binaural Cues

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.

An extension of the PEAQ measure by a binaural hearing model

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.

Comparison of supervised and semi-supervised beamformers using real audio recordings

In this contribution two different disciplines for designing microphone array beamformers are explored. On the one hand a fixed beamformer based on numerical near field optimization is employed. On the other hand an adaptive beamformer algorithm based on the linearly constrained minimum variance (LCMV) method is applied. For the evaluation, an audio-database for microphone array impulse responses and audio recordings (speech and noise) was created. Different acoustic scenarios were constructed, consisting of various audio sources (desired speaker, interfering speaker and directional noise) distributed around the microphone array at different angles and distances. The algorithms were compared based on both objective measure (signal-to-noise, signal-to-interference and speech distortion, and subjective tests (assessment of sonograms and informal listening tests).

Numerical near field optimization of a non-uniform sub-band filter-and-sum beamformer

A novel near field filter-and-sum beamformer using non uniform frequency sub-bands is presented. The concept is based on numerical optimization of the reception characteristic of the microphone array. In order to improve the reception characteristic over frequency and space, a non uniform filterbank is utilized to subdivide the frequency range. Individual optimization processes for each sub-band result in a clearly improved reception characteristic. The new system is able to closely approximate a target (independently of the frequency) which can be defined according to the application.

Noise-shaping for closed-loop Multi-Channel Linear Prediction

In this paper, a novel noise-shaping method for Multi-Channel Linear Prediction (MCLP) is presented. Without special consideration, the quantization noise of the prediction error poses a serious problem in multi-channel prediction as each noise component distorts the reconstruction of every channel at the decoder.