标题： MOVER：结合多个会议识别系统 显示英文标题

标题： MOVER: Combining Multiple Meeting Recognition Systems

摘要： 在本文中，我们提出了会议识别输出投票误差减少（MOVER），一种用于会议识别任务的新型系统组合方法。尽管有结合说话人分离（例如，DOVER）或自动语音识别（ASR）系统（例如，ROVER）输出的方法，MOVER 是第一个可以结合在说话人分离和 ASR 方面都不同的会议识别系统输出的方法。MOVER 通过一个五阶段过程结合具有不同时间间隔和说话人标签的假设，包括说话人对齐、段落分组、词语和时间组合等。在 CHiME-8 DASR 任务和 NOTSOFAR-1 任务的多通道轨道上的实验结果表明，MOVER 可以成功结合多个具有不同说话人分离和识别输出的会议识别系统，在两个任务上相对于最先进系统分别实现了 9.55% 和 8.51% 的相对 tcpWER 改进。 显示英文摘要

摘要： In this paper, we propose Meeting recognizer Output Voting Error Reduction (MOVER), a novel system combination method for meeting recognition tasks. Although there are methods to combine the output of diarization (e.g., DOVER) or automatic speech recognition (ASR) systems (e.g., ROVER), MOVER is the first approach that can combine the outputs of meeting recognition systems that differ in terms of both diarization and ASR. MOVER combines hypotheses with different time intervals and speaker labels through a five-stage process that includes speaker alignment, segment grouping, word and timing combination, etc. Experimental results on the CHiME-8 DASR task and the multi-channel track of the NOTSOFAR-1 task demonstrate that MOVER can successfully combine multiple meeting recognition systems with diverse diarization and recognition outputs, achieving relative tcpWER improvements of 9.55 % and 8.51 % over the state-of-the-art systems for both tasks.