4 papers
Fairness Evaluation of Edge-AI Implementation for Cleft Lip and Palate Speech ASR
Susmita Bhattacharjee, Himashri Deka, H. S. Shekhawat +1
Automatic speech recognition (ASR) remains challenging for individuals with cleft lip and palate (CLP) because of limited pathological speech data and large variations in speech ch…
Normal-Anchored First-Order Model-Agnostic Meta-Learning based Whisper Fine-Tuning for Enhancing Fairness of Cleft Lip and Palate Speech Recognition
Susmita Bhattacharjee, Jagabandhu Mishra, H. S. Shekhawat +2
Automatic speech recognition (ASR) for cleft lip and palate (CLP) speech is difficult because acoustic and articulatory patterns vary across severity levels. This variability reduc…
Parameter-Efficient Fine-Tuning of Foundation Models for CLP Speech Classification
Susmita Bhattacharjee, Jagabandhu Mishra, H. S. Shekhawat +1
We propose the use of parameter-efficient fine-tuning (PEFT) of foundation models for cleft lip and palate (CLP) detection and severity classification. In CLP, nasalization increas…
Improving ASR Fairness for Cleft Lip and Palate Speech: A Study on Severity-Aware Data Mixing
Susmita Bhattacharjee, Jagabandhu Mishra, H. S. Shekhawat +2
Speech produced by individuals with cleft lip and palate (CLP) is often hypernasal (and sometimes breathy) due to structural anomalies, yielding shifts in formant structure that de…