  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.
