Speech Intent Classification

Speech intent classification aims to automatically determine the user's intention from spoken language, a crucial task for applications like voice assistants and smart home devices. Current research focuses on improving accuracy and efficiency, exploring end-to-end models using architectures like Conformers and Transformers, often initialized with pre-trained speech recognition encoders. This field is significant due to its potential to enhance human-computer interaction, particularly by addressing challenges like language diversity and the limitations of current automatic speech recognition systems, leading to more robust and inclusive voice-controlled applications.