@techreport{oai:ipsj.ixsq.nii.ac.jp:00231268,
 author = {何, 嘉俊 and 楊, 沢坤 and 戸田, 智基 and Jiajun, He and Zekun, Yang and Tomoki, Toda},
 issue = {10},
 month = {Nov},
 note = {Automatic speech recognition (ASR) systems often suffer from errors, particularly when recognizing rare words. These errors can be detrimental to downstream tasks such as keyword spotting and language understanding. To alleviate this issue, we propose an ASR error correction method that improves rare word recognition based on error detection and context-aware error correction. Our proposed method limits decoding to only the positions where corrections are required to minimize unnecessary computations. A rare word list is also used to provide additional contextual information for the model to correct errors related to rare words. Experimental results demonstrate that our proposed method outperforms previous works by a large margin in word error rate (WER) on five public datasets while also maintaining a reasonable inference speed. Additionally, the proposed method shows reasonable robustness across different ASR systems., Automatic speech recognition (ASR) systems often suffer from errors, particularly when recognizing rare words. These errors can be detrimental to downstream tasks such as keyword spotting and language understanding. To alleviate this issue, we propose an ASR error correction method that improves rare word recognition based on error detection and context-aware error correction. Our proposed method limits decoding to only the positions where corrections are required to minimize unnecessary computations. A rare word list is also used to provide additional contextual information for the model to correct errors related to rare words. Experimental results demonstrate that our proposed method outperforms previous works by a large margin in word error rate (WER) on five public datasets while also maintaining a reasonable inference speed. Additionally, the proposed method shows reasonable robustness across different ASR systems.},
 title = {誤り検出とコンテキスト適応誤り訂正による音声認識における希少語認識精度改善},
 year = {2023}
}