Keyword Enrollment

Keyword enrollment in keyword spotting (KWS) systems focuses on efficiently and accurately identifying user-defined words within audio streams, often using text-based input for enrollment. Current research emphasizes improving feature extraction techniques (e.g., using multitaper mel-spectrograms or shifted delta coefficients), developing energy-efficient models (like those implemented on neuromorphic processors), and employing advanced deep learning architectures such as recurrent neural networks, transformers, and connectionist temporal classification (CTC) for improved accuracy and robustness against noise and adversarial attacks. This field is crucial for advancing personalized voice-controlled devices and applications, particularly in resource-constrained environments, by enabling more flexible and user-friendly interaction.