6 citations · 14 across the 12 of their papers we have counts for
12 papers
Speaker Verification Under Real Classroom Conditions for English Speech
Saba Tabatabaee, Jing Liu, Meghavarshini Krishnaswamy +1
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…
Multimodal Speaker Identification in Classroom Environments
Michael L. Chrzan, Meghavarshini Krishnaswamy, Robert Gibboni +3
Automated analysis of K-12 classroom dynamics faces challenges due to background noise and variable child speech, often confounding acoustic-only models. This study evaluates a mul…
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…
RealClass: A Framework for Classroom Speech Simulation with Public Datasets and Game Engines
Ahmed Adel Attia, Jing Liu, Carol Espy Wilson
The scarcity of large-scale classroom speech data has hindered the development of AI-driven speech models for education. Classroom datasets remain limited and not publicly availabl…
SimClass: A Classroom Speech Dataset Generated via Game Engine Simulation For Automatic Speech Recognition Research
Ahmed Adel Attia, Jing Liu, Carl Espy-Wilson
The scarcity of large-scale classroom speech data has hindered the development of AI-driven speech models for education. Public classroom datasets remain limited, and the lack of a…
Abstract Sound Fusion with Unconditional Inversion Models
Jing Liu, Enqi Lian, Moyao Deng
An abstract sound is defined as a sound that does not disclose identifiable real-world sound events to a listener. Sound fusion aims to synthesize an original sound and a reference…
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…
CPT-Boosted Wav2vec2.0: Towards Noise Robust Speech Recognition for Classroom Environments
Ahmed Adel Attia, Dorottya Demszky, Tolulope Ogunremi +2
Creating Automatic Speech Recognition (ASR) systems that are robust and resilient to classroom conditions is paramount to the development of AI tools to aid teachers and students.…
Continued Pretraining for Domain Adaptation of Wav2vec2.0 in Automatic Speech Recognition for Elementary Math Classroom Settings
Ahmed Adel Attia, Dorottya Demszky, Tolulope Ogunremi +2
Creating Automatic Speech Recognition (ASR) systems that are robust and resilient to classroom conditions is paramount to the development of AI tools to aid teachers and students.…
The Promises and Pitfalls of Using Language Models to Measure Instruction Quality in Education
Paiheng Xu, Jing Liu, Nathan Jones +2
Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and…
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…