5 papers · 1 filter
Speaker Verification Under Real Classroom Conditions for English Speech
Saba Tabatabaee, Jing Liu, Meghavarshini Krishnaswamy +2
Developing speaker verification (SV) models that are robust to classroom noise and effective across both children and adult speakers is critical for AI tools supporting educational…
Articulation-Informed ASR: Integrating Articulatory Features into ASR via Auxiliary Speech Inversion and Cross-Attention Fusion
Ahmed Adel Attia, Jing Liu, Carol Espy Wilson
Prior works have investigated the use of articulatory features as complementary representations for automatic speech recognition (ASR), but their use was largely confined to shallo…
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…
From Weak Labels to Strong Results: Utilizing 5,000 Hours of Noisy Classroom Transcripts with Minimal Accurate Data
Ahmed Adel Attia, Dorottya Demszky, Jing Liu +1
Recent progress in speech recognition has relied on models trained on vast amounts of labeled data. However, classroom Automatic Speech Recognition (ASR) faces the real-world chall…
Kid-Whisper: Towards Bridging the Performance Gap in Automatic Speech Recognition for Children VS. Adults
Ahmed Adel Attia, Jing Liu, Wei Ai +2
Recent advancements in Automatic Speech Recognition (ASR) systems, exemplified by Whisper, have demonstrated the potential of these systems to approach human-level performance give…