3 accepted papers
In this work, we address the challenge of building fair English ASR systems for second-language speakers. Our analysis of widely used ASR models, Whisper and Seamless-M4T, reveals large fluctuations in word error rate (WER) across 26 accent groups, indicating significant fairness gaps. To mitigate t…
How far have we come in mitigating performance disparities across genders in multilingual speech recognition? We compare the impact on gender disparity of different fine-tuning algorithms for automated speech recognition across model sizes, languages and gender. We look at both performance-focused a…
Multimodal speech emotion recognition (MSER) is an emerging and challenging field of research due to its more robust characteristics than unimodal. However, in multimodal approaches, the interactive relations for model building using different modalities of speech representations for emotion recogni…