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eess.AS2025
Unified Learnable 2D Convolutional Feature Extraction for ASR
Peter Vieting, Benedikt Hilmes, Ralf Schlüter +1
Neural front-ends represent a promising approach to feature extraction for automatic speech recognition (ASR) systems as they enable to learn specifically tailored features for dif…
eess.AS2025
Regularizing Learnable Feature Extraction for Automatic Speech Recognition
Peter Vieting, Maximilian Kannen, Benedikt Hilmes +2
Neural front-ends are an appealing alternative to traditional, fixed feature extraction pipelines for automatic speech recognition (ASR) systems since they can be directly trained…