We evaluate how well LLMs understand African American Language (AAL) in comparison to
their performance on White Mainstream English (WME), the encouraged" standard" form of …

The automatic identification of foreign accents can play a crucial role in various speech
systems, including speaker identification, e-learning, telephone banking, and more …

Underperformance of ASR systems for speakers of African American Vernacular English
(AAVE) and other marginalized language varieties is a well-documented phenomenon, and …

We introduce a new dataset of conversational speech representing English from India,
Nigeria, and the United States. The Multi-Dialect Dataset of Dialogues (MD3) strikes a new …

This paper 1 presents a novel system which utilizes acoustic, phonological,
morphosyntactic, and prosodic information for binary automatic dialect detection of African …

Recently, the widespread use of social media and easy access to the Internet have brought
about a significant transformation in the type of textual data available on the Web. This …

This paper evaluates an innovative framework for spoken dialect density prediction on
children's and adults' African American English. A speaker's dialect density is defined as the …

Abstract Major Depressive Disorder (MDD) is a prevalent mental illness that affects a
significant portion of the global population. Despite its severity, traditional diagnostic …

The potential of speech technology to improve educational outcomes has been a topic of
great interest in recent years. For example, automatic speech recognition (ASR) systems …

Abstract In American English, there are multifarious accents, and one of the outstanding
ones is African American English (AAE). Within African American English, there exist …