Jia Cui

TL;DR: It is shown that with knowledge distillation, information from multiple acoustic models like very deep VGG networks and Long Short-Term Memory models can be used to train standard convolutional neural network (CNN) acoustic models for a variety of systems requiring a quick turnaround.

TL;DR: The RNA binding proteins (RBPs) and microRNAs (miRNAs) that mediate post-transcriptional regulation of the anti-apoptotic BCL2 family members are discussed and their roles and impact on alternative splicing, mRNA turnover, and mRNA subcellular localization are described.

TL;DR: This paper examines the impact of multilingual acoustic representations on Automatic Speech Recognition (ASR) and keyword search (KWS) for low resource languages in the context of the OpenKWS15 evaluation of the IARPA Babel program and shows that these multilingual representations significantly improve ASR and KWS performance.

TL;DR: This work proposes to use an input-feeding architecture which feeds not only the previous context vector but also the previous decoder hidden state information as inputs to the decoder, based on a better hypothesis generation scheme for sequential minimum Bayes risk (MBR) training of sequence-to-sequence models.

TL;DR: This paper investigates the problem of extending data fusion methodologies from Information Retrieval for Spoken Term Detection on low-resource languages in the framework of the IARPA Babel program, and describes a number of alternative methods improving keyword search performance.