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Automatic literacy assessment technology can help children acquire reading skills by providing teachers valuable feedback in a repeatable, consistent manner. Recent research efforts have concentrated on detecting mispronunciations during word-reading and sentence-reading tasks. These token-level assessments are important since they highlight specific errors made by the child. However, there is also...
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predicting the ambient context surrounding an agent, both human and machine. Our method extends the online adaptive Gaussian Mixture model technique to model variations in the background audio. We propose a method for learning...
The ability to identify speech acts reliably is desirable in any spoken language system that interacts with humans. Minimally, such a system should be capable of distinguishing between question-bearing turns and other types of utterances. However, this is a non-trivial task, since spontaneous speech tends to have incomplete syntactic, and even ungrammatical, structure and is characterized by disfluencies,...
The goal of this work is to build a real-time emotion detection system which utilizes multi-modal fusion of different timescale features of speech. Conventional spectral and prosody features are used for intra-frame and supra-frame features respectively, and a new information fusion algorithm which takes care of the characteristics of each machine learning algorithm is introduced. In this framework,...
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