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For professional quality transcription of audio signals, a floating point representation can give substantial savings over a straight binary representation. This paper shows, based on psychoacoustic data of masking noise, how floating point mantissa length, radix value, and exponent length can be arrived at. Listening tests, using real time computer generated music, yielded excellent agreement to the calculated values.
Author (s): Lee, Francis F.;
Lipschutz, David;
Affiliation:
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA
(See document for exact affiliation information.)
AES Convention: 55
Paper Number:1190
Publication Date:
1976-10-06
DOI:
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Lee, Francis F.; Lipschutz, David; 1976; Floating Point Encoding for Transcription of High Fidelity Audio Signals [PDF]; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA; Paper 1190; Available from: https://aes.org/publications/elibrary-page/?id=2224
Lee, Francis F.; Lipschutz, David; Floating Point Encoding for Transcription of High Fidelity Audio Signals [PDF]; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA; Paper 1190; 1976 Available: https://aes.org/publications/elibrary-page/?id=2224
@inproceedings{Lee1976floating,
title={{Floating Point Encoding for Transcription of High Fidelity Audio Signals}},
author={Lee, Francis F. and Lipschutz, David},
year={1976},
month={oct},
booktitle={Journal of the Audio Engineering Society},
publisher={Paper 1190; AES Convention 55; October 1976},
number={1190},
organization={AES},
}
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