Speaker Diarization With Lexical Information
Abstract
This work presents a novel approach to leverage lexical information for speaker diarization. We introduce a speaker diarization system that can directly integrate lexical as well as acoustic information into a speaker clustering process. Thus, we propose an adjacency matrix integration technique to integrate word level speaker turn probabilities with speaker embeddings in a comprehensive way. Our proposed method works without any reference transcript. Words, and word boundary information are provided by an ASR system. We show that our proposed method improves a baseline speaker diarization system solely based on speaker embeddings, achieving a meaningful improvement on the CALLHOME American English Speech dataset.
Cite
@article{arxiv.1811.10761,
title = {Speaker Diarization With Lexical Information},
author = {Tae Jin Park and Kyu Han and Ian Lane and Panayiotis Georgiou},
journal= {arXiv preprint arXiv:1811.10761},
year = {2019}
}
Comments
This version removed by arXiv administrators because the author did not have the right to agree to our license at the time of submission