Journal of the Audio Engineering Society

2007 May - Volume 55 Number 5


Background, Concept, and Architecture for the Recent MPEG Surround Standard on Multichannel Audio Compression

Authors: Breebaart, Jeroen; Hotho, Gerard; Koppens, Jeroen; Schuijers, Erik; Oomen, Werner; Van De Par, Steven

An overview of the recently finalized ISO/MPEG standard for multichannel audio compression MPEG Surround is provided. This audio compression scheme enables backwardcompatible multichannel audio coding and transmission at unsurpassed coding efficiency. This is achieved by generating a mono, stereo, or matrixed-surround compatible down mix, which can be transmitted using any existing mono or stereo service, extended with a small amount of parametric side information that describes the perceptually relevant spatial properties of the original multichannel content. The concepts behind spatial parameterization are outlined, and the architecture of the MPEG Surround system is explained. Results of subjective evaluations are included to demonstrate its efficiency.

Forensic Enhancement of Digital Audio Recordings

Authors: Koenig, Bruce E.; Lacey, Douglas S.; Killion, Steven A.

A protocol is described to improve the voice intelligibility of investigative and other forensic audio recordings collected via digital recording systems, whether audio only or audio/video units. Sections are included on the differences between analog and digital recordings used in the forensic field, appropriate laboratory space, applicable equipment and software, enhancement examination procedures, enhancement examples, evidence handling, and expert testimony.

Intelligent Preprocessing and Classification of Audio Signals

Authors: Bai, Mingsian R.; Chen, Meng-chun

An audio processor that integrates intelligent classification and preprocessing algorithms is presented. Audio features in the time and frequency domains are extracted and processed prior to classification. Classification algorithms, including the nearest neighbor rule (NNR), artificial neural networks (ANN), fuzzy neural networks (FNN), and hidden Markov models (HMM), are used to classify and identify singers and musical instruments. A training phase is required to establish a feature space template, followed by a test phase in which the audio features of the test data are calculated and matched to the feature space template. In addition to audio classification, the proposed system provides several independent component analysis (ICA)-based preprocessing functions for blind source separation, voice removal, and noise reduction. The proposed techniques were applied to process various kinds of audio program materials. The test results reveal that the performance of the methods is satisfactory, but varies slightly with the algorithm and program materials used in the tests.

[Engineering Report] The robust estimation of the frequency of some sinusoidal components is a major prerequisite for many applications, such as in sinusoidal sound modeling, where the estimation often has to be done with low complexity, on short-term spectra. Besides the estimators proposed in the literature, a class known as phase-based estimators is described. It is proven that five of these estimators are equivalent, at least in theory. In-depth practical experiments demonstrate that these estimators perform roughly similarly in practice, although small differences remain, differences that are most probably due to numerical properties of the mathematical operators used in their implementation.

[Feature] Live sound was a big feature of the 121st Convention held recently in San Francisco. Here we provide a round up of the key issues discussed at a number of the live sound seminars there, including the use of wireless microphones, electroacoustic enhancement, digital distribution, and touring systems.

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