Speech Task

Speech task research focuses on developing robust and efficient models for various auditory processing needs, ranging from automatic speech recognition (ASR) and speech translation to more complex tasks like spoken language understanding and sleepiness detection. Current research emphasizes large language models (LLMs) adapted for speech, often employing techniques like dual encoders, efficient adapters, and self-supervised learning to improve performance and reduce computational costs across diverse languages and datasets. These advancements are significant because they enable more accurate and accessible speech technologies with applications in healthcare, education, and communication, particularly in low-resource settings.