ASR System

Automatic Speech Recognition (ASR) systems aim to accurately transcribe spoken language into text, driving applications like virtual assistants and transcription services. Current research emphasizes improving ASR accuracy and efficiency across diverse languages and speaker demographics, focusing on model architectures like Transformers and connectionist temporal classification, and incorporating techniques such as contrastive learning, language model integration, and data augmentation to address challenges like low-resource languages and noisy audio. These advancements are crucial for broadening access to voice-enabled technologies and improving the accuracy and fairness of speech processing across various contexts.