five

GALE Phase 1 Chinese Broadcast Conversation Parallel Text - Part 1

收藏
DataCite Commons2021-07-01 更新2025-04-16 收录
下载链接:
https://catalog.ldc.upenn.edu/LDC2009T02
下载链接
链接失效反馈
官方服务:
资源简介:
<h3>Introduction:</h3> <p> GALE Phase 1 Chinese Broadcast Conversation Parallel Text - Part 1, Linguistic Data Consortium (LDC) catalog number LDC2009T02 and ISBN 1-58563-499-9, contains transcripts and English translations of 20.4 hours of Chinese broadcast conversation programming from China Central TV (CCTV) and Phoenix TV. It does not contain the audio files from which the transcripts and translations were generated. GALE Phase 1 Chinese Broadcast Conversation Parallel Text - Part 1, along with other corpora, was used as training data in year 1 (Phase 1) of the DARPA-funded GALE program. </p> <h3>Source Data:</h3> <p> A total of 20.4 hours of Chinese broadcast conversation programming were selected from two sources: CCTV (a broadcaster from Mainland China), and Phoenix TV (a Hong Kong -based satellite TV station). The transcripts and translations represent recordings of eight different programs. </p> <p>A manual selection procedure was used to choose data appropriate for the GALE program, namely conversation (talk) programs focusing on current events. Stories on topics such as sports, entertainment and business were excluded from the data set. The following table is a summary of the files included in this release. </p> <table><tbody> <tr> <td width="108"> <p> Source </p> </td> <td width="164"> <p> Program </p> </td> <td width="162"> <p> Epoch (YYYY.MM) </p> </td> <td width="96"> <p> #hours </p> </td> <td width="105"> <p> #characters </p> </td> </tr> <tr> <td rowspan="2" width="108"> <p> CCTV </p> </td> <td width="164"> <p> Across China </p> </td> <td width="162"> <p> 2005.08 </p> </td> <td width="96"> <p> 1.0 </p> </td> <td width="105"> <p> 9,924 </p> </td> </tr> <tr> <td width="164"> <p> Todays Focus </p> </td> <td width="162"> <p> 2005.11 </p> </td> <td width="96"> <p> 2.2 </p> </td> <td width="105"> <p> 33,805 </p> </td> </tr> <tr> <td colspan="1" rowspan="6" width="108"> <p> Phoenix TV </p> </td> <td width="164"> <p> Asian Journal </p> </td> <td width="162"> <p> 2005.09 </p> </td> <td width="96"> <p> 2.2 </p> </td> <td width="105"> <p> 26,656 </p> </td> </tr> <tr> <td width="164"> <p> Behind the Headlines </p> </td> <td width="162"> <p> 2005.03 - 2005.11 </p> </td> <td width="96"> <p> 1.5 </p> </td> <td width="105"> <p> 17,933 </p> </td> </tr> <tr> <td> <p> A Date With Lu Yu </p> </td> <td> <p> 2005.09 - 2005.10 </p> </td> <td> <p> 7.1 </p> </td> <td> <p> 89,987 </p> </td> </tr> <tr> <td> <p> News Hacker </p> </td> <td> <p> 2005.03 - 2005.10 </p> </td> <td> <p> 2.3 </p> </td> <td> <p> 39,388 </p> </td> </tr> <tr> <td> <p> Newsline </p> </td> <td> <p> 2005.10 - 2005.11 </p> </td> <td> <p> 1.6 </p> </td> <td> <p> 15,496 </p> </td> </tr> <tr> <td> <p> Social Watch </p> </td> <td> <p> 2005.09 - 2005.11 </p> </td> <td> <p> 2.5 </p> </td> <td> <p> 29,159 </p> </td> </tr> </tbody></table><h3>Transcription:</h3> <p> The selected audio snippets were carefully transcribed by LDC annotators and professional transcription agencies following LDCs Quick Rich Transcription specification. Manual sentence units/segments (SU) annotation was also performed as part of the transcription task. Three types of end of sentence SU are identified: </p> <ul> <li> <p>statement SU</p> </li> <li> <p>question SU</p> </li> <li> <p>incomplete SU</p> </li> </ul><h3>Translation:</h3> <p> After transcription and SU annotation, files were reformatted into a human-readable translation format and assigned to professional translators for careful translation. Translators followed LDCs GALE Translation guidelines which describe the makeup of the translation team, the source data format, the translation data format, best practices for translating certain linguistic features (such as names and speech disfluencies) and quality control procedures applied to completed translations. </p> <h3>TDF Format:</h3> <p> All final data are in Tab Delimited Format (TDF). TDF is compatible with other transcription formats, such as the Transcriber format and AG format, and it is easy to process. </p> <p> Each line of a TDF file corresponds to a speech segment and contains 13 tab delimited fields: </p> <table width="259"><tbody> <tr> <td> <p><strong> Field</strong></p> </td> <td> <p><strong>Data Type</strong></p> </td> </tr> <tr> <td><p> file </p></td> <td><p>unicode </p></td> </tr> <tr> <td><p>channel </p></td> <td><p>int </p></td> </tr> <tr> <td><p>start </p></td> <td><p>float </p></td> </tr> <tr> <td><p>end </p></td> <td><p>float </p></td> </tr> <tr> <td><p>speaker </p></td> <td><p>unicode </p></td> </tr> <tr> <td><p>speakerType </p></td> <td><p>unicode </p></td> </tr> <tr> <td><p> speakerDialect </p></td> <td><p>unicode </p></td> </tr> <tr> <td><p>transcript </p></td> <td><p>unicode </p></td> </tr> <tr> <td><p>section </p></td> <td><p>int </p></td> </tr> <tr> <td><p>turn </p></td> <td><p>int </p></td> </tr> <tr> <td><p>segment </p></td> <td><p>int </p></td> </tr> <tr> <td><p>sectionType </p></td> <td><p>unicode </p></td> </tr> <tr> <td><p>suType </p></td> <td><p>unicode </p></td> </tr> </tbody></table><p> A source TDF file and its translation are the same except that the transcript in the source TDF is replaced by its English translation. </p> <h3>Sponsorship</h3> <p> This work was supported in part by the Defense Advanced Research Projects Agency, GALE Program Grant No. HR0011-06-1-0003. The content of this publication does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. </p> <h3>Samples</h3> For an example of the data in this corpus, please examine these images of the <a href="./desc/addenda/LDC2009T02_source.png" rel="nofollow">source</a> and<a href="./desc/addenda/LDC2009T02_trans.png" rel="nofollow"> translation</a>. </br> Portions © 2005 China Central TV, © 2005 Phoenix TV, © 2005 - 2007, 2009 Trustees of the University of Pennsylvania.
提供机构:
Linguistic Data Consortium
创建时间:
2020-11-30
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作