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The Speakers in the Wild (SITW) speaker recognition database contains hand-annotated speech samples from open-source media for the purpose of benchmarking text-independent speaker recognition technology on single and multi-speaker audio acquired across unconstrained or “wild” conditions. The...

Sep, 2016
In Proceedings
Topics:
412

(A brief blurb that is used when this item is shown in search results or featured on other pages. Will be cut off after 300 characters when displayed on other pages) We introduce the SRI speech-based collaborative learning corpus, a novel collection designed for the investigation and measurement of...

Sep, 2016
Article
Topics:
412

In this paper, we present the SRI system submission to the NIST OpenSAD 2015 speech activity detection (SAD) evaluation.

Sep, 2016
In Proceedings
Topics:
412

We propose to demonstrate the Open Language Interface for Voice Exploitation (OLIVE) speech-processing system, which SRI International developed under the DARPA Robust Automatic Transcription of Speech (RATS) program. The technology underlying OLIVE was designed to achieve robustness to high levels...

Sep, 2016
In Proceedings
Topics:
412

The rate at which endangered languages can be documented has been highly constrained by human factors.

Sep, 2016
In Proceedings
Topics:
412

Recognizing speech under high levels of channel and/or noise degradation is challenging.

Sep, 2016
In Proceedings
Topics:
412

The newly collected Speakers in the Wild (SITW) database was central to a text-independent speaker recognition challenge held as part of a special session at Interspeech 2016. The SITW database is composed of audio recordings from 299 speakers collected from open source media, with an average of 8...

Sep, 2016
In Proceedings
Topics:
412

This article is concerned with the issue of calibration in the context of Deep Neural Network (DNN) based approaches to speaker recognition. DNNs have provided a new standard in technology when used in place of the traditional universal background model (UBM) for feature alignment, or to augment...

Sep, 2016
In Proceedings
Topics:
412

The introduction of deep neural networks has significantly improved automatic speech recognition performance.

Sep, 2016
In Proceedings
Topics:
412

This work investigates whether nonlexical information from speech can automatically predict the quality of small-group collaborations.

Sep, 2016
Technical Report
412

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