3 accepted papers
Automatic speech recognition (ASR) in far-field reverberant environments, especially when involving natural conversational multiparty speech conditions, is challenging even with the state-of-the-art recognition methodologies. The two main issues are artifacts in the signal due to reverberation and t…
The environmental robustness of DNN-based acoustic models can be significantly improved by using multi-condition training data. However, as data collection is a costly proposition, simulation of the desired conditions is a frequently adopted strategy. In this paper we detail a data augmentation appr…
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…