中文连续唇读识别新挑战，数据与模型双升级
CNVSRC 2024: The Second Chinese Continuous Visual Speech Recognition Challenge
- 沿用旧数据集并引入新数据增强多样性
- 改进预处理与模型设计，提升识别准确率
- 适合语音识别、计算机视觉研究者参考
本文介绍了第二届中文连续视觉语音识别挑战赛（CNVSRC 2024），在2023年基础上推动中文大规模连续视觉语音识别（LVC-VSR）研究。挑战赛评估两种测试场景：录音室朗读与网络口语。延续使用原有数据集，包括训练集CN-CVS，开发与评估集CNVSRC-Single/Multi。本次挑战新增两项改进：（1）提供更强基线系统；（2）开放新数据集CN-CVS2-P1用于公开赛道，以提升数据量与多样性。比赛中涌现出多项创新，涵盖数据预处理、特征提取、模型架构与训练策略，进一步推进了中文LVC-VSR的性能边界。更多信息请访问官网。
原文摘要 · Abstract (English)
This paper presents the second Chinese Continuous Visual Speech Recognition Challenge (CNVSRC 2024), which builds on CNVSRC 2023 to advance research in Chinese Large Vocabulary Continuous Visual Speech Recognition (LVC-VSR). The challenge evaluates two test scenarios: reading in recording studios and Internet speech. CNVSRC 2024 uses the same datasets as its predecessor CNVSRC 2023, which involves CN-CVS for training and CNVSRC-Single/Multi for development and evaluation. However, CNVSRC 2024 introduced two key improvements: (1) a stronger baseline system, and (2) an additional dataset, CN-CVS2-P1, for open tracks to improve data volume and diversity. The new challenge has demonstrated several important innovations in data preprocessing, feature extraction, model design, and training strategies, further pushing the state-of-the-art in Chinese LVC-VSR. More details and resources are available at the official website.
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