# OLR 2021 Challenge: Datasets, Rules and Baselines

arXiv: https://arxiv.org/abs/2107.11113 · HTML: https://mlsanity.com/paper/2107.11113/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 24 references that are in the map.
- First posted on arXiv 23 Jul 2021.

## Builds on (most cited first, 8 of 8)

- [SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition](https://mlsanity.com/paper/1904.08779/) (2019)
- [ESPnet: End-to-End Speech Processing Toolkit](https://mlsanity.com/paper/1804.00015/) (2018)
- [Multilingual End-to-End Speech Recognition with A Single Transformer on Low-Resource Languages](https://mlsanity.com/paper/1806.05059/) (2018)
- [AP20-OLR Challenge: Three Tasks and Their Baselines](https://mlsanity.com/paper/2006.03473/) (2020)
- [AP19-OLR Challenge: Three Tasks and Their Baselines](https://mlsanity.com/paper/1907.07626/) (2019)
- [AP16-OL7: A Multilingual Database for Oriental Languages and A Language Recognition Baseline](https://mlsanity.com/paper/1609.08445/) (2016)
- [AP17-OLR Challenge: Data, Plan, and Baseline](https://mlsanity.com/paper/1706.09742/) (2017)
- [AP18-OLR Challenge: Three Tasks and Their Baselines](https://mlsanity.com/paper/1806.00616/) (2018)

## Built on by (most cited first, 5 of 5)

- [Attentive Temporal Pooling for Conformer-based Streaming Language Identification in Long-form Speech](https://mlsanity.com/paper/2202.12163/) (2022)
- [Low-resource speech recognition and dialect identification of Irish in a multi-task framework](https://mlsanity.com/paper/2405.01293/) (2024)
- [Pretraining Approaches for Spoken Language Recognition: TalTech Submission to the OLR 2021 Challenge](https://mlsanity.com/paper/2205.07083/) (2022)
- [Inclusivity of AI Speech in Healthcare: A Decade Look Back](https://mlsanity.com/paper/2505.10596/) (2025)
- [Exploring Energy-Based Models for Out-of-Distribution Detection in Dialect Identification](https://mlsanity.com/paper/2406.18067/) (2024)

## Abstract (arXiv)

This paper introduces the sixth Oriental Language Recognition (OLR) 2021 Challenge, which intends to improve the performance of language recognition systems and speech recognition systems within multilingual scenarios. The data profile, four tasks, two baselines, and the evaluation principles are introduced in this paper. In addition to the Language Identification (LID) tasks, multilingual Automatic Speech Recognition (ASR) tasks are introduced to OLR 2021 Challenge for the first time. The challenge this year focuses on more practical and challenging problems, with four tasks: (1) constrained LID, (2) unconstrained LID, (3) constrained multilingual ASR, (4) unconstrained multilingual ASR. Baselines for LID tasks and multilingual ASR tasks are provided, respectively. The LID baseline system is an extended TDNN x-vector model constructed with Pytorch. A transformer-based end-to-end model is provided as the multilingual ASR baseline system. These recipes will be online published, and available for participants to construct their own LID or ASR systems. The baseline results demonstrate that those tasks are rather challenging and deserve more effort to achieve better performance.