Frequency-Dependent Amplitude Panning for the Stereophonic Image Enhancement of Audio Recorded Using Two Closely Spaced Microphones

Abstract

Abstract:In this paper, we propose a new frequency-dependent amplitude panning method for stereophonic image enhancement applied to a sound source recorded using two closely spaced omni-directional microphones. The ability to detect the direction of such a sound source is limited due to weak spatial information, such as the inter-channel time difference (ICTD) and inter-channel level difference (ICLD). Moreover, when sound sources are recorded in a convolutive or a real room environment, the detection of sources is affected by reverberation effects. Thus, the proposed method first tries to estimate the source direction depending on the frequency using azimuth-frequency analysis. Then, a frequency-dependent amplitude panning technique is proposed to enhance the stereophonic image by modifying the stereophonic law of sines. To demonstrate the effectiveness of the proposed method, we compare its performance with that of a conventional method based on the beamforming technique in terms of directivity pattern, perceived direction, and quality degradation under three different recording conditions (anechoic, convolutive, and real reverberant). The comparison shows that the proposed method gives us better stereophonic images in a stereo loudspeaker reproduction than the conventional method without any annoying effects.

Configuration-Invariant Sound Localization Technique Using Azimuth-Frequency Representation and Convolutional Neural Networks

“…However, the azimuth-frequency representation can be also generated by the attenuation term [13]. In addition, this azimuth-frequency representation can be utilized for the frequency-dependent amplitude panning to enhance the stereophonic image [14]. When a DNN model is utilized for sound localization, a fixed input size is necessary.…”