RSL2019: A Realistic Speech Localization Corpus
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We present a new database for speech localization that we refer to as Realistic Speech Localization 2019 (RSL2019) corpus. The corpus is designed for the study of sound source localization in real-world applications. The RSL2019 corpus is a continuing effort, which presently contains 22.60 hours of speech data, recorded using a four channel microphone array, and played over a loudspeaker from different directions of arrival (DOA). We consider 180speech utterances spoken by 6 speakers, selected from RSR2015database, which are played over the loudspeaker positioned at different angles and distances from the microphone array. We vary the DOA from 0 to 360 degree angle at an interval of 5degree, at 1 metre and 1.5 metre distance. From each position and DOA, we also record white noise to study the robustness, and time stretched pulse to generate the transfer function for speech localization algorithm. Furthermore, we present the experimental results and analysis on state-of-the-art sound source localization algorithm using the open source HARK toolkit on the created RSL2019 database. This database is provided for research purpose only. If you use this database, please cite the following paper. Rohan Sheelvant, Bidisha Sharma, Maulik Madhavi, Rohan Kumar Das, S.R.M. Prasanna and Haizhou Li, "RSL2019: A Realistic Speech Localization Corpus," 2019 22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA), 2019, pp. 1-6, doi: 10.1109/O-COCOSDA46868.2019.9060842. .
我们提出了一款全新的语音定位数据库，命名为真实场景语音定位2019（Realistic Speech Localization 2019, RSL2019）语料库。该语料库专为真实场景下的声源定位研究设计。RSL2019语料库是一项持续推进的研究资源，当前共收录22.60小时的语音数据：采用四通道麦克风阵列进行录制，语音信号通过扬声器以不同到达方向（Direction of Arrival, DOA）播放。本次实验选取了来自6位发音人的共180条语音语句，这些语音取自RSR2015数据库，并通过位于麦克风阵列不同角度和距离处的扬声器进行播放。我们将到达方向的取值范围设为0°至360°，步长为5°，并设置了1米与1.5米两种播放距离。针对每一组播放距离与到达方向组合，我们额外录制了白噪声以研究算法鲁棒性，同时录制时间拉伸脉冲以生成语音定位算法所需的传递函数。此外，我们基于构建完成的RSL2019数据库，使用开源工具包HARK实现了最先进的声源定位算法，并给出了对应的实验结果与分析。本数据库仅用于学术研究用途。若您使用该数据库，请引用以下论文：罗翰·希尔万特、比迪沙·夏尔马、莫利克·马德哈维、罗翰·库马尔·达斯、S.R.M.普拉萨德与李海洲，《RSL2019: A Realistic Speech Localization Corpus》，2019年第22届东方语音数据库与评估技术协调标准化国际委员会（O-COCOSDA）会议，2019年，第1-6页，DOI: 10.1109/O-COCOSDA46868.2019.9060842。
