Papers › ChunkFormer: Masked Chunking Conformer For Long-Form Speech Transcription

ChunkFormer: Masked Chunking Conformer For Long-Form Speech Transcription

20 Feb 2025arXiv:2502.14673links table onlyarchive 2025-07-28

Khanh Le, Tuan Vu Ho, Dung Tran, Duc Thanh Chau

The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.

Deploying ASR models at an industrial scale poses significant challenges in hardware resource management, especially for long-form transcription tasks where audio may last for hours. Large Conformer models, despite their capabilities, are limited to processing only 15 minutes of audio on an 80GB GPU. Furthermore, variable input lengths worsen inefficiencies, as standard batching leads to excessive padding, increasing resource consumption and execution time. To address this, we introduce ChunkFormer, an efficient ASR model that uses chunk-wise processing with relative right context, enabling long audio transcriptions on low-memory GPUs. ChunkFormer handles up to 16 hours of audio on an 80GB GPU, 1.5x longer than the current state-of-the-art FastConformer, while also boosting long-form transcription performance with up to 7.7% absolute reduction on word error rate and maintaining accuracy on shorter tasks compared to Conformer. By eliminating the need for padding in standard batching, ChunkFormer's masked batching technique reduces execution time and memory usage by more than 3x in batch processing, substantially reducing costs for a wide range of ASR systems, particularly regarding GPU resources for models serving in real-world applications.

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Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Speech Recognition Common Voice vi khanhld/chunkformer-large-vie Test WER 6.66 #1 of 3 Archive leaderboard report
Speech Recognition VIVOS khanhld/chunkformer-large-vie Test WER 4.18 #1 of 3 Archive leaderboard report

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