MoDiCoL: A Modular Diagnostic Continual Learning Dataset for Robust Speech Recognition

1. 1Build a speech recognition model using existing datasets
2. 2Run experiments to evaluate performance under real-world distribution shifts
3. 3Configure MoDiCoL to simulate co-occurrence of factors like noise and accents
4. 4Test the robustness of the model using MoDiCoL
5. 5Apply continual learning techniques to improve model performance

Speech recognition engineers and researchers on a team can benefit from MoDiCoL to develop more robust ASR systems, while data scientists can utilize it to improve model performance under real-world conditions

💡 MoDiCoL's modular design allows for simulation of real-world distribution shifts, enhancing model robustness

💡 MoDiCoL: a new dataset for robust speech recognition under real-world conditions #ASR #speechrecognition