What does "Gradient Episodic Memory" mean?
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Gradient Episodic Memory (GEM) is a method used in machine learning to help models learn new information without forgetting what they have already learned. This is important for tasks like automatic speech recognition, where the system needs to adapt to new data while keeping its previous skills intact.
How It Works
GEM uses a technique called episodic memory, which allows the model to remember past experiences. When the model encounters new tasks, it can refer back to these memories. This process helps the system balance its focus between learning new information and retaining old knowledge.
Importance in Speech Recognition
In speech recognition, GEM helps improve performance in noisy environments. By learning from past experiences and applying them to new situations, the system can understand speech better, even when there are challenges. This makes GEM a valuable tool for creating smarter and more effective speech recognition systems.