mlsanityData to 7 Oct 2026

The SLT 2021 children speech recognition challenge: Open datasets, rules and baselines

arXiv 2011.06724 ↗First posted 13 Nov 2020cs.SD eess.AScited by 8

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Abstract (arXiv)

Automatic speech recognition (ASR) has been significantly advanced with the use of deep learning and big data. However improving robustness, including achieving equally good performance on diverse speakers and accents, is still a challenging problem. In particular, the performance of children speech recognition (CSR) still lags behind due to 1) the speech and language characteristics of children's voice are substantially different from those of adults and 2) sizable open dataset for children speech is still not available in the research community. To address these problems, we launch the Children Speech Recognition Challenge (CSRC), as a flagship satellite event of IEEE SLT 2021 workshop. The challenge will release about 400 hours of Mandarin speech data for registered teams and set up two challenge tracks and provide a common testbed to benchmark the CSR performance. In this paper, we introduce the datasets, rules, evaluation method as well as baselines.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Nov 2020.

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Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 2; 2026: 3.

8 papers.