Problem
Research questions and friction points this paper is trying to address.
Non-verbal vocalizations
Automatic speech recognition
Imbalanced supervision
Long-Tail Rebalancing for Non-Verbal Vocalization-Aware ASR: A Track~1 System for the NVVSpeech Challenge
🤖 AI Summary
为解决非语言发声在自动语音识别中的遗漏问题，提出基于跨数据集标签协调和两阶段采样计划的数据中心方法。
📝 Abstract
Non-verbal vocalizations (NVVs) carry important paralinguistic information but are often omitted by conventional automatic speech recognition (ASR) systems. The ISCSLP NVVSpeech Challenge requires joint transcription of lexical content and 16 NVV categories under limited and highly imbalanced supervision. We present a data-centric NVV-aware ASR pipeline based on cross-dataset label harmonization and a two-stage sampling schedule. We map heterogeneous source labels to the official taxonomy and exclude samples without a reliable mapping. Our schedule first uses square-root category sampling to moderate the long-tailed distribution and then applies uniform-category fine-tuning. On a fixed local validation split, square-root category sampling performs best among the tested single-stage settings. The final two-stage system obtains an official score of 63.86 and ranks fourth in Track 1.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Non-verbal Vocalizations
Cross-dataset Label Harmonization
Two-stage Sampling Schedule
Square-root Category Sampling
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