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.