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Decoding Hidden Heritages in Gaelic Traditional Narrative with Text-Mining and Phylogenetics

用文本挖掘和系统发育学解码盖尔传统叙事中的隐藏遗产

基本信息

批准号：
AH/W001934/1
负责人：
William Lamb
金额：
$ 41.38万
依托单位：
University of Edinburgh
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=AH%2FW001934%2F1
关键词：
Decoding Hidden Heritages Gaelic Traditional

项目摘要

This project will fuse deep, qualitative analysis with cutting-edge computational methods to decode, interpret and curate the hidden heritages of Gaelic traditional narrative. We will provide the most detailed account to date of similarities and differences in the countries' narrative traditions and, by extension, a novel understanding of their joint cultural history. Using recent advances in language technology, we will digitise, convert and make available a vast collection of folklore manuscripts in Irish and Scottish Gaelic. In turn, this new digital resource will catalyse ongoing research into Gaelic speech technology.The main question that this project poses is: What can a large, digital collection of traditional narrative tell us about historical cultural exchanges between Scotland and Ireland? While we will examine different kinds of traditional narrative, we will concentrate upon International Tales in Irish and Scottish Gaelic. International Tales are folk narratives that are widely scattered across the world, such as Cinderella or Snow White. Some are amongst the oldest known facets of human oral culture, dating back 5000 years or more. Due to their age and their tendency to vary geographically, they can tell us a lot about relationships between different settlements of people. In this study, we use them as a vehicle for understanding early communication networks between Scotland and Ireland, as well as those that existed within each country. Through an approach known as text-mining, we will use artificial intelligence to search the tales for similar topics, phrases and other linguistic patterns. The matches that we find between texts will be correlated with what we know about the texts themselves. Using another approach, known as phylogenetic network analysis, we will comb relationships between the texts' themes and the people who produced them: for example, their genders, where they lived and what they did for work. In the end, we will combine the two approaches towards a unified account of Scottish and Irish oral narrative. This work will transform our understanding about Gaelic oral culture and disseminate unique archival material online to a diverse set of end-users. Finally, it will positively impact the sustainability of Gaelic-speaking communities through the creation and further stimulation of important language technologies (e.g. handwriting recognition, machine translation and automatic speech recognition).

该项目将融合深入的定性分析与尖端的计算方法，以解码，解释和策划盖尔传统叙事的隐藏遗产。我们将提供迄今为止最详细的关于两国叙事传统的相似性和差异性的描述，并通过扩展，对他们共同的文化历史进行新颖的理解。利用语言技术的最新进展，我们将数字化，转换和提供大量的爱尔兰和苏格兰盖尔语民间传说手稿。反过来，这一新的数字资源将催化正在进行的研究盖尔语语音技术。该项目提出的主要问题是：一个大型的，数字收集的传统叙事可以告诉我们什么关于苏格兰和爱尔兰之间的历史文化交流？虽然我们将研究不同类型的传统叙事，我们将集中在爱尔兰和苏格兰盖尔语的国际故事。国际故事是广泛分布在世界各地的民间故事，如灰姑娘或白色雪。其中一些是人类口头文化中已知最古老的方面，可以追溯到5000年或更久以前。由于它们的年龄和地理上的差异，它们可以告诉我们很多关于不同定居点之间的关系。在这项研究中，我们使用它们作为了解苏格兰和爱尔兰之间的早期通信网络的工具，以及那些存在于每个国家。通过一种被称为文本挖掘的方法，我们将使用人工智能来搜索故事中类似的主题，短语和其他语言模式。我们在文本之间找到的匹配将与我们对文本本身的了解相关联。使用另一种称为系统发生网络分析的方法，我们将梳理文本主题与制作它们的人之间的关系：例如，他们的性别，他们住在哪里，他们做什么工作。最后，我们将联合收割机的两种方法走向苏格兰和爱尔兰的口头叙事的统一帐户。这项工作将改变我们对盖尔口头文化的理解，并将独特的档案材料在线传播给不同的最终用户。最后，它将通过创造和进一步促进重要的语言技术（例如手写识别、机器翻译和自动语音识别），对盖尔语社区的可持续性产生积极影响。