SBIR/STTR Research Award

System for automatic classification of rodent vocalizations

Award identifier 63280824236dd7778c9f6fa8f3891d85561d838599dccb2b1f4827e3f7808e63Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$617,118

Program and phase

SBIR · Phase I

Award year

2014

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
BIOSPEECH INC
Proposal award date
2014-09-01
Contract end date
2016-08-31
UEI
ZNXDMFF4L5J5
Solicitation number
PA11-134
Topic code
101

Research abstract

DESCRIPTION provided by applicant Depression dementia schizophrenia substance abuse developmental disorders and speech related disabilities can feature impairments in the ability to express emotions Development of treatments for these impairments presents a formidable challenge In this regard several researchers who study rodent models of mental illness have more recently focused upon the frequency modulations associated with rodent ultrasonic vocalizations USVs Measures of USVs are an attractive behavioral phenotype because they model the prosodic deficits in existing mental disorders A critical impasse for researchers is that USV extraction from background noise is difficult and time consuming and the approaches used to classify these calls into categories remain arbitrary Thus most researchers report simple tallies of the numbers of USVs produced by their rodent models We propose a software system that allows the user to efficiently and effectively interrogate rodent vocalization data for prosodic content Our collaboration brings together an expert in mouse social behavior Lahvis with an expert in computational assessment of human prosody van Santen We propose to take advantage of two well defined genetic strains of mouse sociability the C Bl and BALB c strains which have been tested extensively for USVs under highly controlled social conditions With audio recordings of these two strains of mice under conditions of social interaction social solicitation and social isolation we will develop software that automatically segments tracks and classifies mouse USVs from acoustic recordings This software will vastly improve researcher efficiency in academic and industry based analysis of rodent vocalizations It will improve routine USV assessments from counts of call rates toward analyses of frequency modulations within each call Further our software will allow users to classify calls according to mathematical approaches rather than the arbitrary currently used This analytical capacity is not currently available despite broad demand for software with this function The proposed software will provide researchers with a powerful new tool for determining how genetic and pharmacological manipulations moderate vocal patterns It will have widespread value for application in academia and industry PUBLIC HEALTH RELEVANCE There is growing interest in and use of assessments of animal vocalizations to understand animal models of neuropsychiatric illness and speech disorders Critically the computational tools used to analyze these vocalizations are cumbersome and analyses of vocalizations often depend upon highly arbitrary classification schemes Through a collaboration between an expert in rodent social behavior and an expert in computational assessments of human speech we propose to develop software that automatically segments tracks and classifies mouse USVs from acoustic recordings or rodents which will have widespread application for academia and industry

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

15 SBIR/STTR records share this UEI (2005–2019). Reported award amounts total $6,736,710. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Health and Human Services

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