Phoneme Recognition

Phoneme recognition, the task of identifying individual speech sounds, is crucial for various speech processing applications. Current research focuses on improving accuracy and robustness using deep learning models like transformers and conformers, often incorporating self-supervised learning and techniques like data augmentation to address challenges posed by limited data, noisy environments, and cross-lingual variations. These advancements are significant for improving speech recognition systems across languages and dialects, impacting fields such as language learning, accessibility technologies, and forensic analysis. Furthermore, research is exploring multimodal approaches, leveraging visual information to enhance phoneme recognition, particularly in challenging acoustic conditions.