用法语翻译增强字义：一个用于直接语音翻译评估的多模态语料库
Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation
摘要：
口语翻译（spoken language translation，缩写为EMT）中的最近的工作已经尝试在学习或解码期间不使用源语言转录的情况下构建端到端的语音到文本的翻译。然而，虽然大量的并行文本（例如Europarl、OpenSubtitles）可用于训练机器翻译系统，但是不存在包括与目标语言的文本对齐的源语言的语音的大型（100 h）和开源并行语料库。本文试图填补这一空白，增加现有的（单语）语料库：LibriSpeech。该语料库用于自动语音识别，来自LibriVox项目的有声读物，并经过仔细的分段和对齐。在从LibriSpeech中收集与英语有声读物相对应的法语电子书后，我们将句子级别的语音片段与各自的翻译对齐，并获得236 h的可用并行数据。本文介绍了处理的细节，以及进行人工评估的一个小的子集的语料库。该评估表明，自动对齐分数与双语对齐质量的人类判断合理相关。我们相信，这个语料库（这是在线提供）是有用的直接语音翻译或更一般的口语翻译实验的可复制实验。
英文摘要：
Recent works in spoken language translation (SLT) have attempted to build end-to-end speech-to-text translation without using source language transcription during learning or decoding. However, while large quantities of parallel texts (such as Europarl, OpenSubtitles) are available for training machine translation systems, there are no large (100h) and open source parallel corpora that include speech in a source language aligned to text in a target language. This paper tries to fill this gap by augmenting an existing (monolingual) corpus: LibriSpeech. This corpus, used for automatic speech recognition, is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. After gathering French e-books corresponding to the English audio-books from LibriSpeech, we align speech segments at the sentence level with their respective translations and obtain 236h of usable parallel data. This paper presents the details of the processing as well as a manual evaluation conducted on a small subset of the corpus. This evaluation shows that the automatic alignments scores are reasonably correlated with the human judgments of the bilingual alignment quality. We believe that this corpus (which is made available online) is useful for replicable experiments in direct speech translation or more general spoken language translation experiments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
