Equality, Diversity and Inclusion (EDI) is an important agenda across every field [1] throughout the world. Language as a major part of communication should be inclusive and treat everyone with equality. Today’s large internet community uses language technology (LT) and has a direct impact on people across the globe. EDI is crucial to ensure everyone is valued and included, so it is necessary to build LT that serves this purpose. Recent results have shown that big data and deep learning are entrenching existing biases and that some algorithms are even naturally biased due to problems such as ‘regression to the mode’. Our focus is on creating LT that will be more inclusive of gender [2], racial [3], sexual orientation [4], persons with disability [5,6]. The workshop will focus on creating speech and language technology to address EDI not only in English, but also in less resourced languages.

The broader objective of LT-EDI-2023 will be 

• To investigate challenges related to speech and language resource creation for EDI.

• To promote research in inclusive LT.

• To adopt and adapt appropriate LT models to suit EDI.

• To provide opportunities for researchers from the LT community around the world to collaborate with other researchers to identify and propose possible solutions for the challenges of  EDI.

Our workshop theme focuses on being more inclusive and providing a platform for researchers to create LT of a more inclusive nature. We hope that through these engagements we can develop LT tools to be more inclusive of everyone, including marginalized people.

Call for Papers:

Our main theme in this workshop is equality, diversity, and inclusivity in LT. We invite researchers and practitioners to submit papers reporting on these issues and datasets to avoid these issues. We also encourage qualitative studies related to these issues and how to avoid them. LT-EDI-2023 welcomes theoretical and practical paper submissions on any languages that contribute to research in Equality, Diversity and Inclusion. We will particularly encourage studies that address either practical application or improving resources.

Topics of interest include, but are not limited to:

• Data set development to include EDI

• Gender inclusivity in LT  

• LGBTQ+ inclusivity in LT 

• Racial inclusivity in LT 

• Persons with disability inclusivity in LT

• Speech and language recognition for minority groups 

• Unconscious bias and how to avoid them in natural language processing, machine learning  and other LT technologies. 

• Tackling rumors and fake news about gender, racial, and LGBTQ+ minorities. 

• Tackling discrimination against gender, racial, and LGBTQ+ minorities.