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By Wen Wang, Haibo Li, Heng Ji

We propose approaches improving statistical machine translation (SMT) performance, by developing name-aware language model adaptations and sparse features, in addition to extracting nameaware translation grammar and rules, adding name phrase table, and name translation driven decoding.

Dec, 2015
In Proceedings
418
By Takaaki Hori, Zhuo Chen, Hakan Erdogan, John R. Hershey, Jonathan Le Roux, Vikramjit Mitra, Shinji Watanabe

This paper introduces the MERL/SRI system designed for the 3rd CHiME speech separation and recognition challenge (CHiME-3).

Dec, 2015
In Proceedings
418
By Vikramjit Mitra, Horacio Franco

Convolutional deep neural networks (CDNNs) have consistently shown more robustness to noise and background contamination than traditional deep neural networks (DNNs).

Dec, 2015
In Proceedings
418
By Luciana Ferrer, Yun Lei, Mitchell McLaren, Nicolas Scheffer

This paper compares different approaches for using deep neural networks (DNNs) trained to predict senone posteriors for the task of spoken language recognition (SLR).

Oct, 2015
Article
418
By Dimitra Vergyri, Bruce Knoth, Elizabeth Shriberg, Vikramjit Mitra, Mitchell McLaren

There is a critical need for detection and monitoring of Post-Traumatic Stress Disorder (PTSD) in both military and civilian populations.

Sep, 2015
In Proceedings
418

We introduce a new dataset for the study of the effect of highly non-stationary noises on language recognition (LR) performance.

Sep, 2015
In Proceedings
418
By Andreas Tsiartas, Andreas Kathol, Elizabeth Shriberg, Massimiliano de Zambotti, Adrian Willoughby

Most research on detecting a speaker’s cognitive state when interacting with a dialog system has been based on selfreports, or on hand-coded subjective judgments based on audio or audio-visual observations.

Sep, 2015
In Proceedings
418

We investigate two systems for automatic disfluency detection on English and Mandarin conversational speech data.

May, 2015
In Proceedings
418

The recent application of deep neural networks (DNN) to speaker identification (SID) has resulted in significant improvements over current state-of-the-art on telephone speech.

Apr, 2015
In Proceedings
418
By Vikramjit Mitra, Elizabeth Shriberg, Dimitra Vergyri, Bruce Knoth

Research on detecting depression from speech has advanced in recent years, but most work has focused on the analysis of one corpus at a time.

Apr, 2015
In Proceedings
418

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