Deep learning, as one of the most currently remarkable machine learning techniques, has
achieved great success in many applications such as image analysis, speech recognition …

We describe the latest version of Microsoft's conversational speech recognition system for
the Switchboard and CallHome domains. The system adds a CNN-BLSTM acoustic model to …

Conversational speech recognition has served as a flagship speech recognition task since
the release of the Switchboard corpus in the 1990s. In this paper, we measure the human …

Conversational speech recognition has served as a flagship speech recognition task since
the release of the Switchboard corpus in the 1990s. In this paper, we measure a human …

Next POI recommendation has been studied extensively in recent years. The goal is to
recommend next POI for users at specific time given users' historical check-in data …

Current research into spoken language translation (SLT), or speech-to-text translation, is
often hampered by the lack of specific data resources for this task, as currently available SLT …

Since convolutional neural networks (CNNs) achieved top performance on the ImageNet
task in 2012, deep learning has become the preferred approach to addressing computer …

This paper advances the design of CTC-based all-neural (or end-to-end) speech
recognizers. We propose a novel symbol inventory, and a novel iterated-CTC method in …

In this paper we show how we have achieved the state-of-the-art performance on the
industry-standard NIST 2000 Hub5 English evaluation set. We explore densely connected …

In this paper we describe an extension of the Kaldi software toolkit to support neural-based
language modeling, intended for use in automatic speech recognition (ASR) and related …