Download Synthetic Transaural Audio Rendering (STAR): a Perceptive Approach for Sound Spatialization The principles of Synthetic Transaural Audio Rendering (STAR) were first introduced at DAFx-06. This is a perceptive approach for sound spatialization, whereas state-of-the-art methods are rather physical. With our STAR method, we focus neither on the wave field (such as HOA) nor on the sound wave (such as VBAP), but rather on the acoustic paths traveled by the sound to the listener ears. The STAR method consists in canceling the cross-talk signals between two loudspeakers and the ears of the listener (in a transaural way), with acoustic paths not measured but computed by some model (thus synthetic). Our model is based on perceptive cues, used by the human auditory system for sound localization. The aim is to give the listener the sensation of the position of each source, and not to reconstruct the corresponding acoustic wave or field. This should work with various loudspeaker configurations, with a large sweet spot, since the model is neither specialized for a specific configuration nor individualized for a specific listener. Experimental tests have been conducted in 2015 and 2019 with different rooms and audiences, for still, moving, and polyphonic musical sounds. It turns out that the proposed method is competitive with the state-of-the-art ones. However, this is a work in progress and further work is needed to improve the quality.
Download First-Order Ambisonic Coding with PCA Matrixing and Quaternion-Based Interpolation We present a spatial audio coding method which can extend existing speech/audio codecs, such as EVS or Opus, to represent first-order ambisonic (FOA) signals at low bit rates. The proposed method is based on principal component analysis (PCA) to decorrelate ambisonic components prior to multi-mono coding. The PCA rotation matrices are quantized in the generalized Euler angle domain; they are interpolated in quaternion domain to avoid discontinuities between successive signal blocks. We also describe an adaptive bit allocation algorithm for an optimized multi-mono coding of principal components. A subjective evaluation using the MUSHRA methodology is presented to compare the performance of the proposed method with naive multi-mono coding using a fixed bit allocation. Results show significant quality improvements at bit rates in the range of 52.8 kbit/s (4 × 13.2) to 97.6 kbit/s (4 × 24.4) using the EVS codec.