Enrollment Utterance

Enrollment utterances, short audio samples used to create speaker profiles for various applications, are a central focus in speaker recognition and related fields. Current research emphasizes improving the robustness and accuracy of systems using enrollment data, exploring techniques like data augmentation, and developing novel model architectures such as joint speaker encoder and neural back-end models, or asymmetric enrollment-verification frameworks with post-training embedding alignment. These advancements aim to enhance the performance of speaker verification, identification, and personalization in speech-based systems, impacting areas like security, accessibility, and personalized services.