AP16-OL7: A Multilingual Database for Oriental Languages and A Language Recognition Baseline
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Abstract (arXiv)
We present the AP16-OL7 database which was released as the training and test data for the oriental language recognition (OLR) challenge on APSIPA 2016. Based on the database, a baseline system was constructed on the basis of the i-vector model. We report the baseline results evaluated in various metrics defined by the AP16-OLR evaluation plan and demonstrate that AP16-OL7 is a reasonable data resource for multilingual research.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Sep 2016.
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Citing papers per year: 2021: 3; 2022: 3; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
7 papers.
- 2021OLR 2021 Challenge: Datasets, Rules and Baselinescited by 5
- 2021Oriental Language Recognition (OLR) 2020: Summary and Analysiscited by 2
- 2021Dynamic Multi-scale Convolution for Dialect Identificationcited by 2
- 2022Pretraining Approaches for Spoken Language Recognition: TalTech Submission to the OLR 2021 Challengecited by 2
- 2022An Overview of Indian Spoken Language Recognition from Machine Learning Perspectivecited by 2
- 2022A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognitioncited by 1
- 2026Speech-Driven End-to-End Language Discrimination towards Chinese Dialectscited by 0
- 2026Speech-Driven End-to-End Language Discrimination towards Chinese Dialects17 Jun 2026
- 2022An Overview of Indian Spoken Language Recognition from Machine Learning Perspective30 Nov 2022
- 2022Pretraining Approaches for Spoken Language Recognition: TalTech Submission to the OLR 2021 Challenge14 May 2022
- 2022A Discriminative Hierarchical PLDA-based Model for Spoken Language Recognition4 Jan 2022
- 2021Dynamic Multi-scale Convolution for Dialect Identification2 Aug 2021
- 2021OLR 2021 Challenge: Datasets, Rules and Baselines23 Jul 2021
- 2021Oriental Language Recognition (OLR) 2020: Summary and Analysis5 Jul 2021