SBIR/STTR Research Award

Subvocal Speech for Augmentative and Alternative Communication

Award identifier 452d20972b5389a66af023ac848f7f9741f2cc2debb229077e5d421235ab50baAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,432,973

Program and phase

SBIR · Phase II – Direct to Phase II

Award year

2015

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
ALTEC, INC
Proposal award date
2015-09-01
Contract end date
2018-02-28
UEI
C14QW1FDLCA8
Solicitation number
PAR14-088
Topic code
NIDCD

Research abstract

DESCRIPTION provided by applicant This Phase II SBIR is prompted by the need for more effective Augmentative and Alternative Communication AAC devices for persons unable to communicate through vocalization The project follows our preliminary work which convincingly demonstrated that surface electromyographic sEMG signals recorded from speech articulation muscles can provide a new and effective form of communication without vocalization Because sEMG based speech recognition does not rely on acoustic excitation of the vocal tract it is readily applicable to recognizing subvocal i e mouthed speech Subvocal speech is therefore an obvious alternative form of communication for patients with laryngectomy The goal of this project is to deliver a pre commercial wearable subvocal speech recognition SSR system operating on an Android mobile device Smartphone that can provide non speakers with a laryngectomy the ability to produce hands free intelligible communication in the home community or over the phone The project is well positioned for direct Phase II development Proof of principal and reduced risk have been achieved on two fronts i wireless sensor designs have been successfully implemented in a rudimentary prototype that improves the task of recording sEMG signals from articulatory muscles of the face and neck and ii the most advanced SSR engine to date has been formulated to achieve accurate recognition of subvocal continuous speech from a word vocabulary tested on unimpaired speakers as well as from people with laryngectomy Phase II will advance these technologies by reducing the requisite sensor set to just facial muscle sites which will be integrated into a pre commercial device for use by non speakers with a laryngectomy Aim will consolidate the individual sEMG sensors into a conformable facial interface and combine the acquired signals into a data stream for Bluetooth connectivity to the Android device running the SSR software The resulting data acquisition system will be encapsulated bench tested and evaluated on subjects with a laryngectomy Aim will create an advanced SSR engine for laryngectomy users that will reduce the requisite number of sensors from to a sub set of on the face while attaining a recognition performance for words at an error rate less than The impact of this innovation is that it provides laryngectomy users with an alternative form of speech that a overcomes the limitations of current automated speech recognition ASR systems that are microphone dependent b is hands free compared to electrolarynx technologies requiring handheld contact c does not suffer from poor intelligibility or the need for surgical interventio and maintenance as with current voice prostheses and d is readily adaptable as a man machine interface for AAC devices PUBLIC HEALTH RELEVANCE We propose an automated speech recognition ASR system that uses the electrical signals from speech articulation muscles during subvocal i e mouthed speech to enable non speakers with a laryngectomy to communicate The Subvocal Speech Recognition System will improve upon current methods of augmentative and alternative communication AAC technologies by offering a non invasive hands free device that produces intelligible speech The impact will improve the quality of life of people with a laryngectomy and lead to alternative methods for interfacing with computers and machines by people with other speech disorders or limited motor function

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

32 SBIR/STTR records share this UEI (1998–2023). Reported award amounts total $27,032,486. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Health and Human Services, Department of Defense

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.