Continuous Speech

Continuous speech processing focuses on analyzing and understanding spoken language as a continuous stream, rather than isolated segments. Current research emphasizes developing robust models that handle the complexities of real-world speech, including noise, variations in speaker characteristics, and the need for efficient processing. This involves leveraging deep learning architectures like transformers and recurrent neural networks, along with novel algorithms for tasks such as keyword spotting, speech-to-text conversion, and brain-computer interfaces. Advances in this field have significant implications for improving human-computer interaction, assistive technologies for individuals with speech impairments, and enhancing our understanding of speech perception in the brain.