# A Psychoacoustic-Based Multiple Audio Object Coding Approach via Intra-Object Sparsity
## 1 Introduction
The latest MPEG-H 3D audio coding standard incorporates the existing MPEG technology components to provide universal means for carriage of channel-based, object-based and Higher Order Ambisonics (HOA) based inputs [15]. Both MPEG-Surround (MPEG-S) and SAOC are included in MPEG-H 3D audio standard. Recently, a Psychoacoustic-based Analysis-By-Synthesis (PABS) method [16, 17] was proposed for encoding multiple speech objects, which could compress four simultaneously occurring speech sources in two downmix signals relied on inter-object sparsity [18]. However, with the number of objects increases, the inter-object sparsity becomes weakened, which leads to quality loss of decoded signal. In our previous work [19, 20, 21], a multiple audio objects encoding approach was proposed based on intra-object sparsity. Unlike the inter-object sparsity employed in PABS framework, this encoding scheme exploited the sparseness of object itself. That is, in a certain domain, an object signal can be represented by a small number of time-frequency instants. The evaluation results validated that this intra-object based approach achieved a better performance than PABS algorithm and retain the superior perceptual quality of the decoded signals. However, the aforementioned technique still has some restrictions which leads to a sub-optimum solution for object compression. Firstly, Short Time Fourier Transform (STFT) is chosen as the linear time-frequency transform to analyze audio objects. Yet the energy compaction capability of STFT is not optimal. Secondly, the above object encoding scheme concentrated on the features of object signal itself without considering the psychoacoustic, thus it is not an optimal quantization means for Human Auditory System (HAS). This paper expands on the contributions in [19]. Based on intra-object sparsity, we propose a novel encoding scheme for multiple audio objects to further optimize our previous proposed approach and minimize the quality loss caused by compression. Firstly, by exploiting intra-object sparsity in the Modified Discrete Cosine Transform (MDCT) domain, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. Secondly, psychoacoustic model is utilized in the proposed codec to accomplish an optimal quantization for HAS. Hence, a Psychoacoustic-based Time-Frequency (TF) instants sorting algorithm is proposed for extracting the dominant TF instants in the MDCT domain. Furthermore, by utilizing these extracted TF instants, we propose a fast algorithm of Number of Preserved Time-Frequency Bins (_NPTF_, defined in Appendix A) allocation strategy to ensure a balanced perception quality for all object signals. Finally, the downmix signal can be further encoded via SQVH technique at desirable bitrate and the side information is transmitted in a lossless manner. In addition, a comparative study of intra-object sparsity of audio signal in the STFT domain and MDCT domain is presented via statistical analysis. The results show that audio objects have sparsity-promoting property in the MDCT domain, which means that a greater data compression ratio can be achieved. The remainder of the paper is structured as follows: Section 2 introduces the architecture of the encoding framework in detail. Experimental results are presented and discussed in Section 3, while the conclusion is given in Section 4. Appendix A investigates the sparsity of audio objects in the STFT and MDCT domain, respectively.