Dhananjay Ram

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Sparse representation has been shown to be a powerful mod-eling framework for classification and detection tasks. In this paper, we propose a new keyword detection algorithm based on sparse representation of the posterior exemplars. The posterior exemplars are phone conditional probabilities obtained from a deep neural network. This method relies on the(More)
We cast the query by example spoken term detection (QbE-STD) problem as subspace detection where query and background subspaces are modeled as union of low-dimensional subspaces. The speech exemplars used for subspace model-ing are class-conditional posterior probabilities estimated using deep neural network (DNN). The query and background training(More)
This work demonstrates an application of different real-time speech technologies, exploited in an online gaming scenario. The game developed for this purpose is inspired by the famous television based quiz-game show, " Who wants to be a millionaire " , in which multiple-choice questions of increasing difficulty are asked to the participant. Text-to-speech(More)
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