Locata Challenge-Evaluation Tasks and Measures
Locata Challenge-Evaluation Tasks and Measures
复制标题
DOI：
10.1109/iwaenc.2018.8521288
复制
发表时间：
2018-09
期刊：
影响因子：
--
通讯作者：
C. Evers;Heinrich W. Löllmann;H. Mellmann;Alexander Schmidt;Hendrik Barfuss;P. Naylor;Walter Kellermann
中科院分区：
文献类型：
--
作者：
C. Evers;Heinrich W. Löllmann;H. Mellmann;Alexander Schmidt;Hendrik Barfuss;P. Naylor;Walter Kellermann
声源定位和跟踪算法提供了声环境中活动声源位置信息的估计。尽管在研究界取得了巨大的进步和极大的兴趣，但迄今为止，还没有对使用共同录音数据库的各种方法进行全面的基准测试。IEEE-AASP声源定位和跟踪挑战赛（LOCATA）的目标是客观地对最先进的定位和跟踪算法进行基准测试，该算法使用开放访问的录音数据语料库，用于音频和声学信号处理应用中通常遇到的场景。挑战任务范围从使用静态麦克风阵列定位单个源到使用移动麦克风阵列跟踪多个移动源。本文概述了挑战任务，描述了用于评估LOCATA挑战的性能度量，并展示了开发数据集的基线结果。
Sound source localization and tracking algorithms provide estimates of the positional information about active sound sources in acoustic environments. Despite substantial advances and significant interest in the research community, a comprehensive benchmarking campaign of the various approaches using a common database of audio recordings has, to date, not been performed. The aim of the IEEE-AASP Challenge on sound source localization and tracking (LOCATA) is to objectively benchmark state-of-the-art localization and tracking algorithms using an open-access data corpus of recordings for scenarios typically encountered in audio and acoustic signal processing applications. The challenge tasks range from the localization of a single source with a static microphone array to tracking of multiple moving sources with a moving microphone array. This paper provides an overview of the challenge tasks, describes the performance measures used for evaluation of the LOCATA Challenge, and presents baseline results for the development dataset.