Lena Foundation

Nuance Communications, Inc.

Sharmistha Sarkar Gray

Terrance D Paul

Dongxin D Xu

Jeffrey A Richards

Umit Yapanel

Jill S Gilkerson

Dushyant Sharma

Patrick A Naylor

Uwe Helmut Jost

Umit Yapenel

A method, computer program product, and computer system for measuring, by a computing device, a plurality of Room Impulse Responses (RIRs) associated with a set of two or more microphones. At least a portion of the RIRs may be augmented. At least the portion of the RIRs may be converted to their respective Relative Transfer Function (RTF) representations. The RTF representations may be applied to training data to generate an acoustic model for automatic speech recognition.

System and method for array data simulation and customized acoustic modeling for ambient ASR

A method of assessing expressive language development of a key child. The method can include processing an audio recording taken in a language environment of the key child to identify segments of the audio recording that correspond to vocalizations of the key child. The method also can include applying an adult automatic speech recognition phone decoder to the segments of the audio recordings to identify each occurrence of a plurality of phone categories and to determine a duration for each of the plurality of phone categories. The method additionally can include determining a duration distribution for the plurality of phone categories based on the durations for the plurality of phone categories. The method further can include using the duration distribution for the plurality of phone categories in an age-based model to assess the expressive language development of the key child. The age-based model is selected based on a chronological age of the key child and the age-based model includes a plurality of different weights associated with the plurality of phone categories. Other embodiments are described.

System and method for assessing expressive language development of a key child

A method of determining an emotion of an utterance. The method can include receiving the utterance at a processor-based device comprising an audio engine. The method also can include extracting emotion-related acoustic features from the utterance. The method additionally can include comparing the emotion-related acoustic features to a plurality of emotion models that are representative of emotions. The method further can include selecting a model from the plurality of emotion models based on the comparing the emotion-related acoustic features to the plurality of emotion models. The method additionally can include outputting the emotion of the utterance, wherein the emotion corresponds to the selected model. Other embodiments are provided.

System and method for emotion assessment

In some embodiments, a method of creating an automatic language characteristic recognition system. The method can include receiving a plurality of audio recordings. The method also can include segmenting each of the plurality of audio recordings to create a plurality of audio segments for each audio recording. The method additionally can include clustering each audio segment of the plurality of audio segments according to audio characteristics of each audio segment to form a plurality of audio segment clusters. Other embodiments are provided.

Systems and methods for an automatic language characteristic recognition system

In one embodiment, the system and method for expressive language development; 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; and the computer programmed to execute a method that 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 also includes extracting acoustic parameters of the key child recordings and comparing the acoustic parameters of the key child recordings to known acoustic parameters for children. The method returns a determination of a likelihood of autism.

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

Certain aspects and embodiments of the present invention are directed to systems and methods for monitoring and analyzing the language environment and the development of a key child. A key child's language environment and language development can be monitored without placing artificial limitations on the key child's activities or requiring a third party observer. The language environment can be analyzed to identify words, vocalizations, or other noises directed to or spoken by the key child, independent of content. The analysis can include the number of responses between the child and another, such as an adult and the number of words spoken by the child and/or another, independent of content of the speech. One or more metrics can be determined based on the analysis and provided to assist in improving the language environment and/or tracking language development of the key child.

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Dracut, MA, United States of America

Sharmistha Sarkar Gray