ZAEBUC-Spoken：一个多语言多方言的阿拉伯语-英语语音语料库
ZAEBUC-Spoken: A Multilingual Multidialectal Arabic-English Speech Corpus
AI总结：
本文提出多语言多方言阿拉伯语-英语语音语料库ZAEBUC-Spoken，包含12小时会议录音，涵盖多语言、多方言及语码转换，并提供转录指南与方言程度、形态学两层标注，为ASR研究提供挑战性数据集。
摘要：
我们提出了ZAEBUC-Spoken，一个多语言多方言的阿拉伯语-英语语音语料库。该语料库包含十二小时的Zoom会议，涉及多名说话人进行角色扮演，模拟一个工作场景：学生就特定主题进行头脑风暴，然后与一位对话者进行讨论。这些会议涵盖不同主题，并分为具有不同语言设置的阶段。该语料库为自动语音识别（ASR）提出了一个具有挑战性的集合，包括两种语言（阿拉伯语和英语），其中阿拉伯语以多种变体（现代标准阿拉伯语、海湾阿拉伯语和埃及阿拉伯语）发音，英语则带有各种口音。增加了语料库复杂性的是，这些语言和方言之间还存在语码转换。作为我们工作的一部分，我们借鉴既有的转录指南集，提出了一套处理会话语音、语码转换以及两种语言正字法问题的指南。我们进一步用两层标注丰富了该语料库；（1）针对语料库中不同阿拉伯语变体发生混合的部分进行方言程度标注，以及（2）自动形态学标注，包括分词、词形还原和词性标注。
英文摘要：
We present ZAEBUC-Spoken, a multilingual multidialectal Arabic-English speech corpus. The corpus comprises twelve hours of Zoom meetings involving multiple speakers role-playing a work situation where Students brainstorm ideas for a certain topic and then discuss it with an Interlocutor. The meetings cover different topics and are divided into phases with different language setups. The corpus presents a challenging set for automatic speech recognition (ASR), including two languages (Arabic and English) with Arabic spoken in multiple variants (Modern Standard Arabic, Gulf Arabic, and Egyptian Arabic) and English used with various accents. Adding to the complexity of the corpus, there is also code-switching between these languages and dialects. As part of our work, we take inspiration from established sets of transcription guidelines to present a set of guidelines handling issues of conversational speech, code-switching and orthography of both languages. We further enrich the corpus with two layers of annotations; (1) dialectness level annotation for the portion of the corpus where mixing occurs between different variants of Arabic, and (2) automatic morphological annotations, including tokenization, lemmatization, and part-of-speech tagging.
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。
