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arXiv · 2309.08377

DiaCorrect: Error Correction Back-end For Speaker Diarization

Jiangyu Han·Federico Landini·Johan Rohdin·Mireia Diez·Lukas Burget·Yuhang Cao·Heng Lu·Jan Cernocky
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Abstract

In this work, we propose an error correction framework, named DiaCorrect, to refine the output of a diarization system in a simple yet effective way. This method is inspired by error correction techniques in automatic speech recognition. Our model consists of two parallel convolutional encoders and a transform-based decoder. By exploiting the interactions between the input recording and the initial system's outputs, DiaCorrect can automatically correct the initial speaker activities to minimize the diarization errors. Experiments on 2-speaker telephony data show that the proposed DiaCorrect can effectively improve the initial model's results. Our source code is publicly available at https://github.com/BUTSpeechFIT/diacorrect.

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Jiangyu Han, Federico Landini, Johan Rohdin, Mireia Diez, Lukas Burget, Yuhang Cao, Heng Lu, Jan Cernocky. 2023-09-15. DiaCorrect: Error Correction Back-end For Speaker Diarization. https://arxiv.org/abs/2309.08377

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