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Annotating audio data for the presence and location of speech is a time-consuming and therefore costly task.

Sep, 2016
In Proceedings
Topics:
413

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:
413

(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:
413

We present the work done by our group for the 2015 language recognition evaluation (LRE) organized by the National Institute of Standards and Technology (NIST).

Jun, 2016
In Proceedings
413
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
413
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
413

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
413
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
413

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
413

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