5 papers
Objective and Subjective Evaluation of Diffusion-Based Speech Enhancement for Dysarthric Speech
Dimme de Groot, Tanvina Patel, Devendra Kayande +2
Dysarthric speech poses significant challenges for automatic speech recognition (ASR) systems due to its high variability and reduced intelligibility. In this work we explore the u…
How to Evaluate Automatic Speech Recognition: Comparing Different Performance and Bias Measures
Tanvina Patel, Wiebke Hutiri, Aaron Yi Ding +1
There is increasingly more evidence that automatic speech recognition (ASR) systems are biased against different speakers and speaker groups, e.g., due to gender, age, or accent. R…
Loudspeaker Beamforming to Enhance Speech Recognition Performance of Voice Driven Applications
Dimme de Groot, Baturalp Karslioglu, Odette Scharenborg +1
In this paper we propose a robust loudspeaker beamforming algorithm which is used to enhance the performance of voice driven applications in scenarios where the loudspeakers introd…
Good practices for evaluation of machine learning systems
Luciana Ferrer, Odette Scharenborg, Tom Bäckström
Many development decisions affect the results obtained from ML experiments: training data, features, model architecture, hyperparameters, test data, etc. Among these aspects, argua…
Self-supervised Speech Representations Still Struggle with African American Vernacular English
Kalvin Chang, Yi-Hui Chou, Jiatong Shi +4
Underperformance of ASR systems for speakers of African American Vernacular English (AAVE) and other marginalized language varieties is a well-documented phenomenon, and one that r…