7 accepted papers
Pattern classification systems have traditionally been trained using a set of labeled training data and subsequently evaluated using different testing data. The cost of labeling the training data is typically substantial. Online Human-In-The-Loop (HITL) algorithms present an alternate approach that…
Voice type discrimination (VTD) is the task of automatically detecting speech produced in the same room as a recording device ("live speech") among other speech and non-speech noises, such as traffic noises or radio broadcasts ("distractor audio"). Existing work has described methods for performing…
We describe a modulation-domain loss function for deep-learning-based speech enhancement systems. Learnable spectro-temporal receptive fields (STRFs) were adapted to optimize for a speaker identification task. The learned STRFs were then used to calculate a weighted mean-squared error (MSE) in the m…
This paper describes a combination of techniques for improving speech recognition accuracy using two microphones in reverberant and noisy environments. These techniques include both monaural and binaural processing. The first stage is monaural precedence-based processing that enhances the onsets of…
In this paper, we present an algorithm called Reliable Mask Selection-Phase Difference Channel Weighting (RMS-PDCW) which selects the target source masked by a noise source using the Angle of Arrival (AoA) information calculated using the phase difference information. The RMS-PDCW algorithm selects…
While many recently proposed audio declipping algorithms are highly effective in their ability to restore clipped speech, the algorithms' computational complexities inhibit their use in many practical situations. Real-time or nearly real-time performance is impossible using a typical laptop computer…
A group of junior and senior researchers gathered as a part of the 2014 Frederick Jelinek Memorial Workshop in Prague to address the problem of predicting the accuracy of a nonlinear Deep Neural Network probability estimator for unknown data in a different application domain from the domain in which…