Mark Stuart Vinton

Joint optimization of scale factors and Huffman code books for MPEG-4 AAC

This paper addresses the optimization problem of minimizing the distortion subject to a rate constraint for an MPEG-4 Advanced Audio Coding (AAC) encoder. We first develop a mathematical model of the AAC encoding process. In previous work, the joint optimization problem is modeled as a Viterbi search for a cheapest path through a trellis. This method involves an iteration over a Lagrangian multiplier. We improve on this method by deriving a very accurate guess for the value of the final Lagrangian multiplier of the iteration as a function of the Perceptual Entropy of the signal and the given rate constraint. This reduces the complexity of the Trellis Search significantly. Whereas previous methods including the Trellis Search did not provide optimal solutions to the problem of minimizing the distortion subject to a rate constraint, we establish two methods that for the first time solve this problem optimally. Our first method is based on the formulation and solution of a Mixed Integer Linear Program, whereas our second method uses a Dynamic Programming solution that does not rely on the iteration over a Lagrangian multiplier. Based on our optimal methods, we evaluate the performance of the heuristic Two Loop Search (TLS), which is used in most commercial AAC implementations to solve the problem under consideration, and the performance of the Trellis Search.

Delivering Scalable Audio Experiences using AC-4

AC-4 is a state-of-the-art audio codec standardized in ETSI (TS 103 190 and TS 103 190-2) and included in the DVB toolbox (TS 101 154 V2.2.1 and DVB BlueBook A157) and, at the time of writing, is a candidate standard for ATSC 3.0 as per A/342 part 2. AC-4 is an audio codec designed to address the current and future needs of video and audio entertainment services, including broadcast and Internet streaming. As such, it incorporates a number of features beyond the traditional audio coding algorithms, such as capabilities to support immersive and personalized audio, support for advanced loudness management, video-frame synchronous coding, dialog enhancement, etc. This paper will outline the thinking behind the design of the AC-4 codec, explain the different coding tools used, the systemic features included, and give an overview of performance and applications. It further outlines metadata aspects (immersive and personalized, essential for broadcast), metadata carriage, aspects of interchange of immersive programing, as well as immersive playback and rendering.

Blind bandwidth extension using K-means and Support Vector Regression

In this paper, a blind bandwidth extension algorithm for music signals has been proposed. This method applies the K-means algorithm to firstly cluster audio data in the feature space, and constructs multiple envelope predictors for each cluster accordingly using Support Vector Regression (SVR). A set of well-established audio features for Music Information Retrieval (MIR) has been used to characterize the audio content. The resulting system is applied to a variety of music signals without any side information provided. The subjective listening test results show that this method can improve the perceptual quality successfully, but the minor artifacts still leave room for future improvements.

The choice of MPEG-4 AAC encoding parameters as a direct function of the perceptual entropy of the audio signal

This paper proposes a new procedure of low-complexity to determine the encoding parameters for the MPEG-4 AAC encoder under real-time constraints. In particular, it addresses the optimization problem of minimizing the distortion subject to a rate constraint for an MPEG-4 AAC encoder. Existing implementations use the heuristic two loop search to solve this optimization problem. This paper presents a new solution algorithm which achieves distortion values significantly lower than the two loop search and which, due to its low computational complexity, is a promising technology for future AAC implementations. We show via simulations that the technology presented in this paper significantly outperforms previous technologies.