System and method for expressive language, developmental disorder, and emotion assessment

摘要

In one embodiment, a method for detecting autism in a natural language environment using a microphone, sound recorder, and a computer programmed with software for the specialized purpose of processing recordings captured by the microphone and sound recorder combination, the computer programmed to execute the method, includes segmenting an audio signal captured by the microphone and sound recorder combination using the computer programmed for the specialized purpose into a plurality recording segments. The method further includes determining which of the plurality of recording segments correspond to a key child. The method further includes determining which of the plurality of recording segments that correspond to the key child are classified as key child recordings. Additionally, the method includes extracting phone-based features of the key child recordings; comparing the phone-based features of the key child recordings to known phone-based features for children; and determining a likelihood of autism based on the comparing.

主权项

1. A method comprising:
capturing an audio recording from a language environment of a key child; segmenting the audio recording into a plurality of segments using a Minimum Duration Gaussian Mixture Model (MD-GMM) technique, the MD-GMM technique comprising performing a maximum log-likelihood analysis to generate the plurality of segments having a minimum duration constraint; identifying a segment ID for each of the plurality of segments, the segment ID identifying a source for audio in the segment of the plurality of segments; identifying a plurality of key child segments from the plurality of segments, each of the plurality of key child segments having the key child as the segment ID; estimating key child segment characteristics based in part on at least one of the plurality of key child segments, wherein the key child segment characteristics are estimated independent of contents of the plurality of key child segments, wherein the contents are meanings of the plurality of key child segments; determining at least one metric associated with the language environment using the key child segment characteristics; and outputting the at least one metric.