Multiple Vocoder Translation Software Application

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$994,937.00
Award Year:
2008
Program:
SBIR
Phase:
Phase II
Contract:
N00039-09-C-0003
Award Id:
82848
Agency Tracking Number:
N072-135-0211
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
260 Bear Hill Road, Waltham, MA, 02451
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
062172143
Principal Investigator:
John Tardelli
Director, Digital Speech
(781) 933-0069
jdtardelli@arcon.com
Business Contact:
James Brunelle
CFO
(781) 890-3330
jeb@arcon.com
Research Institution:
n/a
Abstract
A set of vocoder translation methods will be developed for use in voice communications applications where different vocoder algorithms are being used across the application. The translation methods will provide reduced complexity and increased performance from that of digital tandem approach. The translations will address system configurations involving both speech model parametric based vocoders and direct waveform representation types of vocoder. The complexity of a translation method for a given configuration will be targeted to be less than that of the corresponding tandem for that configuration. The goal for the performance of the voice communication for a given configuration will be greater than or equal to that of the corresponding digital tandem. Previous research has demonstrated that by adjusting for parametric vocoder algorithm differences in procedures such as pre-emphasis and characteristics such as analysis window size, an increased performance can be achieved by transcoding. In a transcode, the model parameters from the source vocoder are translated to the model parameters of the destination vocoder. For those parametric vocoders that do not incorporate acoustic noise reduction techniques, the performance of specific configuration is limited to that of the lower data rate coder of the configuration. With waveform types of vocoders, with no parametric basis, it is not possible to use a true transcode approach to translation. For theses configurations, smart tandem approaches will be developed. The smart tandems will match the digital speech streams for best performance while reducing complexity with mixed synthesis approaches.

* information listed above is at the time of submission.

Agency Micro-sites


SBA logo

Department of Agriculture logo

Department of Commerce logo

Department of Defense logo

Department of Education logo

Department of Energy logo

Department of Health and Human Services logo

Department of Homeland Security logo

Department of Transportation logo

Enviromental Protection Agency logo

National Aeronautics and Space Administration logo

National Science Foundation logo
US Flag An Official Website of the United States Government