Multi-Channel WSJ Audio

Introduction Multi-Channel WSJ Audio (MCWSJ) was developed by the Centre for Speech Technology Research at The University of Edinburgh and contains approximately 100 hours of recorded speech from 45 British English speakers. Participants read Wall Street Journal texts published in 1987-1989 in three recording scenarios: a single stationary speaker, two stationary overlapping speakers and one single moving speaker. This corpus was designed to address the challenges of speech recognition in meetings, which often occur in rooms with non-ideal acoustic conditions and significant background noise, and may contain large sections of overlapping speech. Using headset microphones represents one approach, but meeting participants may be reluctant to wear them. Microphone arrays are another option. MCWSJ supports research in large vocabulary tasks using microphone arrays. The news sentences read by speakers are taken from WSJCAM0 Cambridge Read News, a corpus originally developed for large vocabulary continuous speech recognition experiments, which in turn was based on CSR-1 (WSJ0) Complete, made available by LDC to support large vocabulary continuous speech recognition initiatives. Data Speakers reading news text from prompts were recorded using a headset microphone, a lapel microphone and an eight-channel microphone array. In the single speaker scenario, participants read from six fixed positions. Fixed positions were assigned for the entire recording in the overlapping scenario. For the moving scenario, participants moved from one position to the next while reading. Fifteen speakers were recorded for the single scenario, nine pairs for the overlapping scenario and nine individuals for the moving scenario. Each read approximately 90 sentences. The audio data are presented as single channel 16kHz flac compressed wav files. Samples Please listen to the below samples. Overlapping Sample Stationary Sample Moving Sample Updates None at this time. Portions © 1987-1989 Dow Jones & Company, Inc., © 2014 University Court of the University of Edinburgh, © 1992-1995, 2014 Trustees of the University of Pennsylvania

简介：多通道华尔街日报语音语料库（Multi-Channel WSJ Audio, MCWSJ）由爱丁堡大学语音技术研究中心开发，收录了来自45名英国英语使用者的约100小时录制语音。参与者需朗读1987至1989年出版的《华尔街日报》文本，共设置三种录制场景：单固定说话者、双固定重叠说话者及单移动说话者。

本语料库旨在应对会议场景下的语音识别挑战——此类场景常处于非理想声学环境，伴随显著背景噪声，且存在大量重叠语音片段。头戴式麦克风虽是一种解决方案，但参会者往往不愿佩戴；麦克风阵列则是另一可选方案。MCWSJ可支撑基于麦克风阵列的大词汇量语音识别研究。

参与者朗读的新闻语句源自WSJCAM0剑桥朗读新闻语料库，该语料库最初为大词汇量连续语音识别实验开发，其本身又基于语言数据联盟（Linguistic Data Consortium, LDC）发布的CSR-1（WSJ0）完整语料库，用于支持大词汇量连续语音识别相关研究项目。

数据：参与者根据提示朗读新闻文本，录制时分别使用头戴式麦克风、领夹式麦克风以及八通道麦克风阵列。单说话者场景中，参与者需在六个固定位置完成朗读；重叠场景中，全程使用固定位置进行录制；移动场景中，参与者需在朗读过程中于不同位置间移动。本次录制共覆盖15名单说话者场景参与者、9组重叠场景说话者对、9名移动场景参与者，每人朗读约90个语句。音频数据以单通道16kHz FLAC压缩WAV格式提供。

示例：请收听以下示例
重叠场景示例
固定场景示例
移动场景示例

更新说明：暂无当前更新。

版权声明：部分内容 © 1987-1989 道琼斯公司（Dow Jones & Company, Inc.），© 2014 爱丁堡大学教务委员会，© 1992-1995、2014 宾夕法尼亚大学董事会。