Publication Details
Diacorrect: Error Correction Back-End for Speaker Diarization
Landini Federico Nicolás (RG SPEECH)
Rohdin Johan Andréas, M.Sc., Ph.D. (DCGM)
DIEZ SÁNCHEZ, M.
Burget Lukáš, doc. Ing., Ph.D. (DCGM)
CAO, Y.
LU, H.
Černocký Jan, prof. Dr. Ing. (DCGM)
Speaker diarization, error correction, conversational telephone speech
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 transformerbased 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.
@inproceedings{BUT189697,
author="HAN, J. and LANDINI, F. and ROHDIN, J. and DIEZ SÁNCHEZ, M. and BURGET, L. and CAO, Y. and LU, H. and ČERNOCKÝ, J.",
title="Diacorrect: Error Correction Back-End for Speaker Diarization",
booktitle="ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
year="2024",
pages="11181--11185",
publisher="IEEE Signal Processing Society",
address="Seoul",
doi="10.1109/ICASSP48485.2024.10446968",
isbn="979-8-3503-4485-1",
url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10446968"
}