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The VOiCES from a Distance Challenge 2019 Evaluation Plan

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arxiv 1902.10828 v1 pith:VCBDGXD5 submitted 2019-02-27 eess.AS cs.SD

The VOiCES from a Distance Challenge 2019 Evaluation Plan

Mahesh Kumar Nandwana , Julien van Hout , Mitchell McLaren , Colleen Richey , Aaron Lawson , Maria Alejandra Barrios This is my paper
classification eess.AS cs.SD
keywords recognitionchallengedistancespeakerspeechareaautomaticdistant
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The "VOiCES from a Distance Challenge 2019" is designed to foster research in the area of speaker recognition and automatic speech recognition (ASR) with the special focus on single channel distant/far-field audio, under noisy conditions. The main objectives of this challenge are to: (i) benchmark state-of-the-art technology in the area of speaker recognition and automatic speech recognition (ASR), (ii) support the development of new ideas and technologies in speaker recognition and ASR, (iii) support new research groups entering the field of distant/far-field speech processing, and (iv) provide a new, publicly available dataset to the community that exhibits realistic distance characteristics.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. BUT VOiCES 2019 System Description

    eess.AS 2019-07 unverdicted novelty 3.0

    BUT reports x-vector systems achieving 1.0% EER via fusion on the fixed condition of the VOiCES 2019 speaker recognition challenge.

  2. The DKU System for the Speaker Recognition Task of the 2019 VOiCES from a Distance Challenge

    eess.AS 2019-07 unverdicted novelty 2.0

    DKU's ResNet-based system with angular softmax and WPE achieves 0.3532 minDCF and 4.96% EER on the VOiCES 2019 evaluation set using cosine scoring.