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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
413

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
413

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

May, 2015
In Proceedings
413

Computational methods for speech-based detection of depression are still relatively new, and have focused on either a standard set of features or on specific additional approaches.

Apr, 2015
In Proceedings
413

We recently proposed the use of coefficients extracted from the 2D discrete cosine transform (DCT) of log Mel filter bank energies to improve speaker recognition over the traditional Mel frequency cepstral coefficients (MFCC) with appended deltas and double deltas (MFCC/deltas).

Apr, 2015
In Proceedings
413

In this paper we propose softSAD: the direct integration of speech posteriors into a speaker recognition system instead of using speech activity detection (SAD).

Apr, 2015
In Proceedings
413

This chapter focuses on the automatic identification of demographic traits and identity in both speech and writing.

Apr, 2015
In Book
413

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
413

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
413

Neural network joint modeling (NNJM) has produced huge improvement in machine translation performance.

Apr, 2015
In Proceedings
413

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