# Quality Enhancement of MPEG-H 3 DA Binaural Rendering Using a Spectral Compensation Technique
## 1 Introduction  
The MPEG-H 3D Audio (3 DA) standard [1] aims to provide immersive 3D audio for high-resolution UHDTVs. It comprises state-of-the-art technologies that support high-efficiency compression and transmission of channel, object-based, SAOC (spatial audio object coding) and HoA (high-order ambisonics) audio formats, and high-quality rendering in various layouts. Recently, the MPEG-H 3 DA system was adopted in TV broadcast standards, e.g., ATSC 3.0 [2] and DVB [3], and in the virtual reality (VR) profile of mobile standard 3 GPP [4]. The MPEG-H decoder can render each audio format on various playback layouts using the format converter, object renderer, SAOC renderer, and HoA renderer. In addition, the standard includes a low-complexity high-quality binaural renderer in response to the increasing use cases of mobile devices. Another important feature of MPEG-H 3 DA is interactivity, i.e., the listener can manipulate each audio scene to the extent allowed by the content creator. A typical use case is to render audio based on three degrees of freedom of the head (i.e., yaw, pitch, and roll rotation). With these advantages, the MPEG-H 3 DA decoder low complexity (LC) profile was selected as a 3 DoF (Degrees of Freedom)/3 DoF + rendering technology for MPEG-I audio standards for augmented reality (AR) and VR. MPEG-H 3 DA performs 3 DoF rendering of object and channel signals [1], using virtual loudspeaker rendering (VLR) [5]. In the VLR, object signals are first converted to virtual channel (loudspeaker) signals using panning techniques, such as 3D vector basic amplitude panning (VBAP) [6] and multidirectional amplitude panning (MDAP) [7]. The virtual channel signals are filtered with low-resolution binaural room transfer function (BRTF) or head-related transfer function (HRTF) and then downmixed to generate the binauralsignal. During this binaural downmixing process, various speaker-to-ear transfer functions corresponding to different acoustics paths are mixed, resulting in the so-called comb filter effect [8]. The primary artifacts of the comb filter effect are spectral coloration and volume degradation, both of which cause inaccurate spatial image position, often significantly [8; 9]. Therefore, to improve the audio quality of MPEG-H 3 DA binaural rendering (BR), it is crucial to prevent the comb filter effect. For the channel signals, the MPEG-H 3 DA decoder performs BR after 'objectizing' channel signals (by regarding channel signals as object signals at the loudspeaker positions). In general, high-quality channel sources include 'artistic intentions', such as EQ, which may prevent the comb filter artifacts. However, 'artistic intents' alone cannot overcome the comb filter effect in every case of 3 DoF rendering of channel sources. This paper presents a rigorous method to improve the sound quality of MPEG-H 3 DA BR. We first propose an efficient gain normalization algorithm that can compensate for the spectral artifacts caused by the comb filter effect. The previous studies on this issue mainly focused on the panning algorithm. In [7; 10], the panning gain ratio was adjusted to improve the sound image localization performance. In [8; 9], a panning gain normalization was used to reduce coloration. However, these methods were developed assuming loudspeaker-based listening environments. In such a case, binaural transfer functions are not considered precisely; hence they only partially prevent the comb filter effect when used for VLR. A baseline solution for this spectral coloration and distortion is active downmixing [11]. Unfortunately, active downmixing does not work when more than one sound object resides in a single processing band, which is common in many audio signals. The proposed algorithm performs spectral compensation in both the panning gain and downmix signal domains. In order to implement frequency dependent compensation on the standard effectively, the MPEG-H 3 DA frequency domain object renderer and binaural renderer working in the 64-band complex quadrature mirror filter (QMF) [12] are used.