1 citations · 1 across the 2 of their papers we have counts for
4 papers
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…
Fusion of Modulation Spectrogram and SSL with Multi-head Attention for Fake Speech Detection
Rishith Sadashiv T N, Abhishek Bedge, Saisha Suresh Bore +3
Fake speech detection systems have become a necessity to combat against speech deepfakes. Current systems exhibit poor generalizability on out-of-domain speech samples due to lack…
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…