Recognition Pipeline

Recognition pipelines encompass the computational processes used to identify patterns in various data types, such as speech, images, and sensor readings. Current research focuses on improving accuracy and robustness by incorporating techniques like judgement mechanisms to correct model errors, leveraging large language models to discover underlying structural patterns, and transferring pre-trained multimodal models to new tasks. These advancements are driving improvements in applications ranging from speech recognition across diverse languages to scene text recognition and activity monitoring in smart homes, ultimately impacting fields like human-computer interaction and assistive technologies.