3 accepted papers
Recognizing not only pre-defined keywords but also continuously expanding new keywords often with limited data has emerged as a main problem in recent keyword spotting research. To address this challenge few-shot class-incremental learning approaches have gained attention initially training models o…
Adaptive S-norm (AS-norm) calibrates automatic speaker verification (ASV) scores by normalizing them utilize the scores of impostors which are similar to the input speaker. However, AS-norm does not involve any learning process, limiting its ability to provide appropriate regularization strength for…
Data augmentation using additive noise is a framework for robustly training automatic speech recognition models. To utilize noise information efficiently, previous studies used an additional branch to classify noise conditions. This added branch has a limited effect on the ASR because it performs in…