RT-03-CTS

The 'RT-03-CTS' dataset is used to evaluate speaker diarization systems and their effectiveness in reducing speaker error rates in automatic speech recognition pipelines.

Papers using RT-03-CTS (4)

SEAL: Speaker Error Correction using Acoustic-conditioned Large Language Models2025Lexical Speaker Error Correction: Leveraging Language Models for Speaker Diarization Error Correction2023AG-LSEC: Audio Grounded Lexical Speaker Error Correction2024Speakers Unembedded: Embedding-free Approach to Long-form Neural Diarization2024