TC-STAR 2005 Evaluation Package - SLT Chinese-to-English

TC-STAR is a European integrated project focusing on Speech-to-Speech Translation (SST). To encourage significant breakthrough in all SST technologies, annual open competitive evaluations are organized. Automatic Speech Recognition (ASR), Spoken Language Translation (SLT) and Text-To-Speech (TTS) are evaluated independently and within an end-to-end system.The first TC-STAR evaluation campaign took place in March 2005. Two core technologies were evaluated during the campaign:• Automatic Speech Recognition (ASR),• Spoken Language Translation (SLT).Each evaluation package includes resources, protocols, scoring tools, results of the official campaign, etc., that were used or produced during the first evaluation campaign. The aim of these evaluation packages is to enable external players to evaluate their own system and compare their results with those obtained during the campaign itself.The speech databases made within the TC-STAR project were validated by SPEX, in the Netherlands, to assess their compliance with the TC-STAR format and content specifications.This package includes the material used for the TC-STAR 2005 Spoken Language Translation (SLT) first evaluation campaign for Spanish-to-English translation. The same packages are available for English (ELRA-E0002), Spanish (ELRA-E0003) and Mandarin Chinese (ELRA-E0004) for ASR and for SLT in 3 directions, English-to-Spanish (ELRA-E0005) and Spanish-to-English (ELRA-E0006).To be able to chain the components, ASR and SLT evaluation tasks were designed to use common sets of raw data and conditions. Two evaluation tasks, common to ASR and SLT, were selected: EPPS (European Parliament Plenary Sessions) task and VOA (Voice of America) task. This package was used within the VOA task and consists of 2 data sets:- Development data set: built upon the ASR development data set, in order to enable end-to-end evaluation. Subsets of 25,000 characters were selected from the VOA verbatim transcriptions. The source texts were then translated into English by two independent translation agencies. All source text sets and reference translations were formatted using the same SGML DTD that has been used for the NIST Machine Translation evaluations.- Test data set: as for the development set, the same procedure was followed to produce the test data, i.e.: subsets of 25.000 characters were selected from the test data set from the manual transcriptions. The source data were then translated into English by two independent agencies

TC-STAR是一项旨在聚焦于语音到语音翻译（SST）的欧洲综合性项目。为促进SST技术领域的重大突破，项目每年组织开放性的竞争性评估活动。自动语音识别（ASR）、口语语言翻译（SLT）以及文本到语音（TTS）的评估独立进行，并在端到端系统中进行综合评估。首次TC-STAR评估活动于2005年3月举行。在此次活动中，对两项核心技术进行了评估：• 自动语音识别（ASR），• 口语语言翻译（SLT）。每个评估包都包含资源、协议、评分工具、官方活动结果等，这些都是在首次评估活动中使用或生成的。这些评估包的目的是使外部参与者能够评估自己的系统，并将自己的结果与活动本身获得的结果进行比较。在TC-STAR项目中创建的语音数据库已由荷兰的SPEX进行验证，以评估其是否符合TC-STAR的格式和内容规范。本包包括用于TC-STAR 2005口语语言翻译（SLT）首次评估活动的材料，针对西班牙语到英语的翻译。相同的包也适用于英语（ELRA-E0002）、西班牙语（ELRA-E0003）和普通话（ELRA-E0004）的ASR以及三种方向的SLT，即英语到西班牙语（ELRA-E0005）和西班牙语到英语（ELRA-E0006）。为了能够串联组件，ASR和SLT评估任务被设计为使用共同的原始数据集和条件。选定了两个对ASR和SLT都通用的评估任务：欧洲议会全体会议（EPPS）任务和美国之音（VOA）任务。本包在VOA任务中使用，包括两个数据集：- 开发数据集：基于ASR开发数据集构建，以实现端到端评估。从VOA逐字转录中选取了25,000个字符的子集。源文本随后由两家独立的翻译机构进行翻译。所有源文本集和参考翻译均使用与NIST机器翻译评估相同的SGML DTD进行格式化。- 测试数据集：与开发集类似，遵循相同的程序生成测试数据，即：从手动转录的测试数据集中选取了25,000个字符的子集。源数据随后由两家独立的机构进行翻译。