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 Chinese-to-English (ELRA-E0007). 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 EPPS 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 words were selected from the EPPS verbatim transcriptions, and from the Final Text Edition documents. The source texts were then the 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 words were selected from the test data set (Parliament’s sessions from 15 to 18 November 2004) both from the manual transcriptions and from the Final Text Edition documents. The source data were then translated into English by two independent agencies.