Tuka Alhanai is a PhD candidate in the department of Electrical Engineering and Computer Science working in the Spoken Language Systems group under the supervision of Dr. James Glass. Tuka applies machine learning in the context of speech and language processing with experience in pronunciation, language, and acoustic modeling, as well as sentiment analysis. Her current work leverages multi-modal data to develop automated tools that assess an individual's emotional and mental well-being, such as depression and dementia, and is currently collaborating with the Framingham Heart Study in this line of research.

Research Areas

Impact Areas



Automatic Speech Recognition

Automatic speech recognition (ASR) has been a grand challenge machine learning problem for decades. Our ongoing research in this area examines the use of deep learning models for distant and noisy recording conditions, multilingual, and low-resource scenarios.


Arabic Language Processing

The Arabic language is spoken by over one billion people around the world. Arabic presents a variety of challenges for speech and language processing technologies. In our group, we have several research topics examining Arabic, including dialect identification, speech recognition, machine translation, and language processing.
Jim Glass