2019 INTERSPEECH INTERSPEECH 2019

The Second DIHARD Challenge: System Description for USC-SAIL Team

Abstract

In this paper, we describe components that form a part of USC-SAIL team’s submissions to Track 1 and Track 2 of the second DIHARD speaker diarization challenge. We describe each module in our speaker diarization pipeline and explain the rationale behind our choice of algorithms for each module, while comparing the Diarization Error Rate (DER) against different module combinations. We propose a clustering scheme based on spectral clustering that yields competitive performance. Moreover, we introduce an overlap detection scheme and a re-segmentation system for speaker diarization and investigate their performances using controlled and in-the-wild conditions. In addition, we describe the additional components that will be integrated to our speaker diarization system. To pursue the best performance, we compare our system with the state-of-the-art methods that are presented in the previous challenge and literature. We include preliminary results of our speaker diarization system on the evaluation data from the second DIHARD challenge.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio