Annotation Graphs and Servers and Multi-Modal Resources

Title: Annotation Graphs and Servers and Multi-Modal Resources

Research Question: How can annotation graphs and servers be used to share and manage linguistic resources for interdisciplinary research?

Methodology: The researchers proposed a common framework for annotation and resource sharing based on annotation graphs and servers. They reviewed examples of data and tools from various fields, such as empirical linguistics, natural language processing, speech recognition, information retrieval, and language teaching.

Results: The review highlighted the common needs and goals among these fields, including the need for language resources, annotations, and consistent processes for extracting relevant observations. The researchers proposed an infrastructure that allows for the annotation of linguistic data and the application of that infrastructure to various fields.

Implications: This infrastructure has the potential to facilitate collaboration and knowledge sharing among diverse research communities. By reusing and reannotating language resources, researchers can save time and resources while benefiting from the results. Additionally, the use of annotation graphs and servers can lead to more accurate and robust language technologies.

Link to Article: https://arxiv.org/abs/0204022v1 Authors: arXiv ID: 0204022v1