Abstract：
Expert testimony is only admissible in common-law systems if it will potentially assist the trier of fact. In order for a forensic-voice-comparison expert\'s testimony to assist a trier of fact, the expert\'s forensic voice comparison should be more accurate than the trier of fact\'s speaker identification. \"Speaker identification in courtroom contexts - Part I\" addressed the question of whether speaker identification by an individual lay listener (such as a judge) would be more or less accurate than the output of a forensic-voice-comparison system that is based on state-of-the-art automatic-speaker-recognition technology. The present paper addresses the question of whether speaker identification by a group of collaborating lay listeners (such as a jury) would be more or less accurate than the output of such a forensic-voice-comparison system. As members of collaborating groups, participants listen to pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case, confer, and make a probabilistic consensus judgement on each pair of recordings. The present paper also compares group-consensus responses with \"wisdom of the crowd\" which uses the average of the responses from multiple independent individual listeners.
摘要：
专家证词只有在可能有助于事实调查的情况下，才能在普通法制度中被接受。为了让法医语音比较专家的证词来帮助调查事实，专家的法医语音比较应该比事实的说话者识别更准确。“法庭环境中的说话者识别-第一部分”解决了一个问题，即个人外行听众（例如法官）的说话者识别是否比基于最先进的自动说话者识别技术的法医语音比较系统的输出更准确。本文解决了一个问题，即一组合作的外行听众（例如陪审团）的说话者识别是否比这种法医语音比较系统的输出更准确。作为合作团体的成员，参与者听成对的录音，这些录音反映了实际情况下有疑问和已知说话者录音的条件，confer,并对每一对录音做出概率一致判断。本文还将群体共识反应与“人群智慧”进行了比较，后者使用了多个独立个体听众的平均反应。
