A multi-attribute subjective evaluation method on binaural 3D audio without reference stimulus

With the rise of the concept of metaverse and the development of virtual reality (VR), the effect of 3D audio has become an important factor which influences the immersive experience. Considering the widely used binaural 3D audio, it's important to evaluate the quality as different representation methods exist. However, there's no reference stimulus when evaluating binaural 3D audio, making it difficult to compare different representation methods. This paper proposes a multi-attribute evaluation method on binaural 3D audio without reference stimulus. Through this method, a comparative experiment with channel-based, scene-based, and object-based binaural 3D audios was conducted. The results prove that binaural 3D audios of these three representation methods are similar in audio quality, but differ greatly in spatial sense, giving a solid data support to the feature comparison of channel-based, scene-based, and object-based methods. It is also proved that the evaluation method is valid through statistical analysis and can be used in other test requirements of binaural 3D audio.