MULTI LINGUAL ASR WITH TRANSFORMERS

Recent research has focused on developing multilingual automatic speech recognition (ASR) systems using Transformer-based models. These models aim to address challenges in training and deploying ASR systems for low- resource languages, adapting to multiple domains and languages, and reducing operational costs. Strategies such as locale-group multilingual Transformer language models, adaptable multi- domain language models, and configurable multilingual models have been proposed to improve the performance and efficiency of multilingual ASR. These advancements demonstrate a concerted effort to overcome the challenges of low-resource languages, domain adaptation, and multilingual speech recognition.