Frequency domain binaural model based on interaural phase and level differences

Abstract

We can communicate with others in a noisy environment. This phenomenon is known as a "Cocktail Party Effect" and is one of the most important binaural functions. This paper addresses a frequency domain binaural model that plays the role of a binaural function based on an interaural phase and level difference. The proposed model is evaluated not only as a front-end of the speech recognition system, but also as a speech enhancer. According to the evaluation, when the direction of arrival of the target signal and noise differs by 10°, recognition rates improve in comparison with the previous time domain binaural model (TDBM) in any cases. Furthermore, recognition rates show more than 90% when the signal to noise ratio (SNR) is higher than approximately 5 dB. On the other hand, SNR and coherence of the frequency domain binaural model, which is obtained for an evaluation of the speech enhancer, show superior results over the TDBM.