5 papers
Towards noise-robust speech inversion through multi-task learning with speech enhancement
Saba Tabatabaee, Carol Espy-Wilson
Recent studies demonstrate the effectiveness of Self Supervised Learning (SSL) speech representations for Speech Inversion (SI). However, applying SI in real-world scenarios remain…
Acoustic to Articulatory Speech Inversion for Children with Velopharyngeal Insufficiency
Saba Tabatabaee, Suzanne Boyce, Liran Oren +2
Traditional clinical approaches for assessing nasality, such as nasopharyngoscopy and nasometry, involve unpleasant experiences and are problematic for children. Speech Inversion (…
Perceptual Ratings Predict Speech Inversion Articulatory Kinematics in Childhood Speech Sound Disorders
Nina R. Benway, Saba Tabatabaee, Dongliang Wang +3
Purpose: This study evaluated whether articulatory kinematics, inferred by Articulatory Phonology speech inversion neural networks, aligned with perceptual ratings of /r/ and /s/ i…
Enhancing Acoustic-to-Articulatory Speech Inversion by Incorporating Nasality
Saba Tabatabaee, Suzanne Boyce, Liran Oren +2
Speech is produced through the coordination of vocal tract constricting organs: lips, tongue, velum, and glottis. Previous works developed Speech Inversion (SI) systems to recover…
FT-Boosted SV: Towards Noise Robust Speaker Verification for English Speaking Classroom Environments
Saba Tabatabaee, Jing Liu, Carol Espy-Wilson
Creating Speaker Verification (SV) systems for classroom settings that are robust to classroom noises such as babble noise is crucial for the development of AI tools that assist ed…