论文标题
SDS-200：瑞士德语对标准德语文本语料库的演讲
SDS-200: A Swiss German Speech to Standard German Text Corpus
论文作者
论文摘要
我们介绍SDS-200，这是瑞士德语言语演讲，标准德语文本翻译，并用言语的方言，年龄和性别信息注释。该数据集允许培训语音翻译，方言识别和语音合成系统等。数据是使用向公众开放的Web记录工具收集的。每个参与者都以标准德语的方式给出了文本，并要求将其翻译成瑞士德语方言，然后再记录下来。为了提高语料库质量，录音得到了其他参与者的验证。该数据包括大约4000名不同演讲者的200小时演讲，并涵盖了瑞士 - 德国方言景观的很大一部分。我们将SDS-200与基线语音翻译模型一起发布，该模型的单词错误率（WER）为30.3，在SDS-200测试集上，单词错误率为30.3，BLEU得分为53.1。此外，我们使用SDS-200微调预先训练的XLS-R模型，达到21.6 WER和64.0 BLEU。
We present SDS-200, a corpus of Swiss German dialectal speech with Standard German text translations, annotated with dialect, age, and gender information of the speakers. The dataset allows for training speech translation, dialect recognition, and speech synthesis systems, among others. The data was collected using a web recording tool that is open to the public. Each participant was given a text in Standard German and asked to translate it to their Swiss German dialect before recording it. To increase the corpus quality, recordings were validated by other participants. The data consists of 200 hours of speech by around 4000 different speakers and covers a large part of the Swiss-German dialect landscape. We release SDS-200 alongside a baseline speech translation model, which achieves a word error rate (WER) of 30.3 and a BLEU score of 53.1 on the SDS-200 test set. Furthermore, we use SDS-200 to fine-tune a pre-trained XLS-R model, achieving 21.6 WER and 64.0 BLEU.
