Automatic analysis of LENA recordings for language assessment in children aged five to fourteen years with application to individuals with autism

Detecting child and adult vocalizations, and computing their characteristics from audio recorded in natural home environments can be useful in many applications. The current study is interested in monitoring children with autism spectrum disorder to ultimately provide outcome measures that can track the efficacy of clinical treatments. In this paper, we show that it is possible to automate detection of child and adult vocalizations from audio recorded in controlled clinic environments as well as in naturalistic home settings. The results show both high precision and recall for children aged five to fourteen years who have been diagnosed with autism. Further, we describe a highly accurate speaker-independent laughter detector for this age group which will be useful for affect estimation.

[1]  M. Soderstrom,et al.  When Do Caregivers Talk? The Influences of Activity and Time of Day on Caregiver Speech and Child Vocalizations in Two Childcare Environments , 2013, PloS one.

[2]  John H. L. Hansen,et al.  Employing speech and location information for automatic assessment of child language environments , 2016, 2016 First International Workshop on Sensing, Processing and Learning for Intelligent Machines (SPLINE).

[3]  Dongxin Xu,et al.  The LENA , 2009 .

[4]  Katarzyna Chawarska,et al.  Parental Recognition of Developmental Problems in Toddlers with Autism Spectrum Disorders , 2007, Journal of autism and developmental disorders.

[5]  Björn W. Schuller,et al.  Recent developments in openSMILE, the munich open-source multimedia feature extractor , 2013, ACM Multimedia.

[6]  Daniel Povey,et al.  The Kaldi Speech Recognition Toolkit , 2011 .

[7]  Jill Gilkerson,et al.  A Social Feedback Loop for Speech Development and Its Reduction in Autism , 2014, Psychological science.

[8]  Mark A. Hall,et al.  Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning , 1999, ICML.

[9]  Catherine Lord,et al.  Annual research review: re-thinking the classification of autism spectrum disorders. , 2012, Journal of child psychology and psychiatry, and allied disciplines.

[10]  James R. Glass,et al.  Unsupervised Methods for Speaker Diarization: An Integrated and Iterative Approach , 2013, IEEE Transactions on Audio, Speech, and Language Processing.