Journal of the Audio Engineering Society

2008 September - Volume 56 Number 9

Papers


Performance Analysis of Digital Loudspeaker Arrays

Authors: Pedersen, Bo Rohde; Kontomichos, Fotios; Mourjopoulos, John

An analysis of digital loudspeaker arrays shows that the ways in which bits are mapped to the drivers influence the quality of the audio result. Specifically, a “bit-summed” rather than the traditional “bit-mapped” strategy greatly reduces the number of times drivers make binary transitions per period of the input frequency. Detailed simulations compare the results for a 32-loudspeaker array with a similar configuration with analog excitation of the drivers. Ideally, drivers in digital arrays should be very small and span a small area, but that sets limits on the low-frequency response.

Split-sideband synthesis (SpSB)—which is related to the well-known principles of waveshaping, single-sideband modulation, and frequency modulation—offers the possibility of creating four independent sideband outputs: upper, lower, odd, and even. Novel spectra and timbres can be created by the way in which these four outputs are combined. As with similar techniques for distortion synthesis, an SpSB process is controlled by the modulator and carrier frequencies as well as the modulation index. The technique can also be used as an adaptive effect applied to arbitrary monophonic signals. A number of sound samples illustrate the technique.

The conventional model of a dynamic moving-coil loudspeaker is improved by incorporating a semi-inductor that results from eddy currents and skin effect in the pole pieces. Highly conductive metals such as aluminum, copper, or silver concentric to the voice coil can be treated as a one-turn secondary in a transformer with the primary of the voice coil. This new model produces more accuracy, as illustrated in a simulation of sound pressure frequency response of a woofer in an enclosure. The model is relevant to all electrodynamic transducers.

System for Automatic Singing Voice Recognition

Authors: Zwan, Pawel; Kostek, Bozena

A neural network was trained and tested to provide automated classification of singing voices, both recognizing voice quality (amateur, semiprofessional, and professional) and voice type (bass, baritone, tenor, alto, mezzo-soprano, and soprano). Parameters related to singing were defined to form feature vectors. Single vowel samples for each singer were judged by six experts to establish a quality index. In a test based on a database of 2690 samples, 90% of the decisions were correct. These results show that it is possible to use neural networks to create an expert system to evaluate singing.

The Future of Home Audio

Authors: Rumsey, Francis

[Feature] Steve Harris held an interesting tutorial on linking up consumer audio systems using networks at the AES 123rd Convention last year in New York. The main points arising from the tutorial are summarized in this article, along with some expanded explanations of the technology and concepts involved. A number of alternative home AV networking developments are also reviewed.

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Standards and Information Documents


AES Standards Committee News

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Features


33rd Conference Report, Denver

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The Future of Home Audio

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126th Convention, Munich, Call for Papers

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36th Conference, Dearborn, Call for Papers

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37th Conference, Denmark, Call for Papers

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Departments


News of the Sections

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Sound Track

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New Products and Developments

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Available Literature

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Upcoming Meetings

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Membership Information

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Advertiser Internet Directory

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In Memoriam

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Sections Contacts Directory

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AES Conventions and Conferences

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Extras


Cover & Sustaining Members List

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AES Officers, Committees, Offices & Journal Staff

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Advertisements

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