SBIR/STTR Research Award

Automatic Spoken Language Recognition for Machine Foreign Language Translation (MFLT)

Award identifier 88e03efcb3812e7cf8090020c54d2aa7d68e3a52a8dc0577fd930d94bcff4a1eAwarding agency Department of Defense · Army

Award amount

$492,615

Program and phase

SBIR · Phase II

Award year

2013

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Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
VOCI TECHNOLOGIES INCORPORATED
Proposal award date
2013-08-29
Contract end date
2015-08-29
UEI
WRL3N9JB4AS9
Solicitation number
2012.1
Topic code
A12-031

Research abstract

Voci Technologies Incorporated (Voci) is partnering with Carnegie Mellon University (CMU) to develop and demonstrate a prototype Automated Spoken Language Recognition System (ASLRS). The ASLRS is specifically designed to enhance the usability of Speech to Speech (S2S) Machine Foreign Language Translation (MFLT) systems for the warfighter. The proposed ASLRS will leverage the Teams existing language identification capabilities, experience, and expertise to fulfill the requirements of an efficient MFLT preprocessor. Best-in-class accuracy will be achieved using a combination of techniques and fusing the results. To meet the real-time requirements, a ground-breaking, patent-pending, multi-language phonetic dictionary capable of doing phonetic recognition in all 6 target languages in a single pass will be utilized. An open-set solution will be provided so that the ASLRS recognizes when an out-of-domain language is spoken. To ensure that the resulting ASLRS is generally applicable, it will be architected to be an open system, ensuring that it is inter-operable with existing MFLT solutions and that it supports the addition of new languages. To ensure that the system provides reliable results, even in noisy environment, the system will incorporate noise robust features. Finally, to address the shortcomings of existing solutions in real-world field conditions, the Team will integrate a learning capability into the ASLRS so that it can adapt to different accents and noise conditions that exist during field use. At the end of Phase II, the Team will demonstrate the prototype ASLRS on a mobile device (e.g., Android smartphone). We believe the final implementation will revolutionize S2S MFLT use in the field.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

6 SBIR/STTR records share this UEI (2012–2016). Reported award amounts total $1,692,874. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Defense

Agency intelligence

Department of Defense

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