Analysis of Infant Babbles
|Harriet J. Fell, Ph.D||College of Computer Science, Northeastern University|
|Linda J. Ferrier, Ph.D..||Speech-Language Pathology and Audiology, Northeastern|
|Dr. Carol Espy-Wilson, Ph.D..||Electrical and Computer Engineering, Boston University|
|Susan G. Worst, M.A.||College of Computer Science. Northeastern University|
|Eric A. Craft M.S.||Electrical and Computer Engineering, Boston University|
|Karen Chenausky, M.S||Speech Technology and Applied Research, Lexington, Massachusetts|
|Joel MacAuslan, Ph.D||Speech Technology and Applied Research, Lexington, Massachusetts|
|Glenna Hennessey M.S.||Speech-Language Pathology and Audiology, Northeastern|
Presented at theAmerican Speech-Language-Hearing Convention November 17, 2000.|
This work was sponsored in part by NIH Grant #R42-HD34686.
AbstractThe Early Vocalization Analyzer (EVA), is a computer program that automatically analyzes digitized recordings of infant vocalizations. EVA is can clinically distinguish typically developing from non-typically developing infants strictly by acoustic analysis of an infant's syllable structure.
BackgroundConsiderable research supports the position that infant vocalizations effectively predict later articulation and language. Intervention to encourage babbling activity in at-risk infants is frequently recommended. However, research and clinical diagnosis of delayed or reduced babbling have so far depended on time-consuming and often unreliable perceptual analyses of tape-recorded infant sounds. While acoustically analyzing infant sounds has provided important information on the early characteristics of infant vocalizations, this information has not yet been used in automatic analysis. We are developing a program, EVA, which automatically analyzes digitized recordings of infant vocalizations.
Here, we report on our progress in extending EVA in two ways:
SubjectsNine typically developing subjects were recorded. Four were male and five female. We are now following five at-risk infants, four are male and one female. Of these infants, one has apraxia, one has Down Syndrome, three, one of whom was premature, show motor delay. Of the fourteen infants, two are African-American and one is Hispanic. All but the Hispanic infant have American-English-speaking parents. Each infant was recorded eight times for 40 minutes, at approximately monthly intervals, from six to thirteen months.
The EVA Software
Landmark DetectorBuilt on the Liu-Stevens Landmark Detection program for adult-speech founded on Stevens' acoustic model of speech production. Central to this theory are landmarks, points in an utterance around which listeners extract information about the underlying distinctive features. They mark perceptual foci and articulatory targets.
The program detects three types of landmarks:
Post-AnalyzerUses landmark types and times output by the Landmark Detection program to:
The Phonetic ClassifierA version of Carol Espy-Wilson's classifier EBS (Event Based System, 1995) has been adapted by Eric Craft, Boston University for use with infant vocalizations. This program labels the following features (see figure 1):
Finding the Vocalizaton Age
Coefficients in the EVA Vocalization Age
Diagnostic Value of the Vocalization AgeThe following graphs show the Vocalization Age versus the Actual Age of the infants in our study. The first graph shows the results for typically developing children only, the second graph for non-typically developing children (a key follows), and the third graph shows both groups of children combined with magenta + marks for the typically developing children and cyan o marks for the non-typically developing children. The lines are at Vocalization Age = Actual Age and at Vocalization Age = Actual Age +/1 one or two standard deviations (1.46 months)
The Non-typical Subjects
Last Updated: November 11, 2000 7:20 p.m.
The URL for this document is: http://www.ccs.neu.edu/home/fell/evaEVAasha2000.html