2 research outputs found
AP17-OLR Challenge: Data, Plan, and Baseline
We present the data profile and the evaluation plan of the second oriental
language recognition (OLR) challenge AP17-OLR. Compared to the event last year
(AP16-OLR), the new challenge involves more languages and focuses more on short
utterances. The data is offered by SpeechOcean and the NSFC M2ASR project. Two
types of baselines are constructed to assist the participants, one is based on
the i-vector model and the other is based on various neural networks. We report
the baseline results evaluated with various metrics defined by the AP17-OLR
evaluation plan and demonstrate that the combined database is a reasonable data
resource for multilingual research. All the data is free for participants, and
the Kaldi recipes for the baselines have been published online.Comment: Submitted to APSIPA ASC 2017. arXiv admin note: text overlap with
arXiv:1609.0844
AP18-OLR Challenge: Three Tasks and Their Baselines
The third oriental language recognition (OLR) challenge AP18-OLR is
introduced in this paper, including the data profile, the tasks and the
evaluation principles. Following the events in the last two years, namely
AP16-OLR and AP17-OLR, the challenge this year focuses on more challenging
tasks, including (1) short-duration utterances, (2) confusing languages, and
(3) open-set recognition. The same as the previous events, the data of AP18-OLR
is also provided by SpeechOcean and the NSFC M2ASR project. Baselines based on
both the i-vector model and neural networks are constructed for the
participants' reference. We report the baseline results on the three tasks and
demonstrate that the three tasks are truly challenging. All the data is free
for participants, and the Kaldi recipes for the baselines have been published
online.Comment: arXiv admin note: substantial text overlap with arXiv:1706.0974