Publications Search | Page 4 | SRI International

Toggle Menu

Publications Search

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
420

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

Apr, 2015
In Book
420

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
420
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
420

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

Apr, 2015
In Proceedings
420
By Vikramjit Mitra, Elizabeth Shriberg

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
420

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
420
By Harish Arsikere, Elizabeth Shriberg, Umut Ozertem

Speech to personal assistants (e.g., reminders, calendar entries, messaging, voice search) is often uttered under cognitive load, causing nonfinal pausing that can result in premature recognition cut-offs.

Mar, 2015
In Proceedings
420
By Andreas Kathol, Elizabeth Shriberg

We describe the SRI BioFrustration Corpus, an inprogress corpus of time-aligned audio, video, and autonomic nervous system signals recorded while users interact with a dialog system to make returns of faulty consumer items.

Mar, 2015
In Proceedings
420

We present a system for detection of lexical stress in English words spoken by English learners. This system was designed to be part of the EduSpeak® computer-assisted language learning (CALL) software.

Feb, 2015
Journal
420

Pages