Transcribed Audio

Transcribed audio research focuses on accurately converting spoken language into text, driving advancements in speech recognition and translation. Current efforts concentrate on developing multilingual models, leveraging large datasets like YouTube videos, and improving efficiency through techniques like knowledge distillation and self-supervised learning with architectures such as autoregressive encoder-decoders and neural machine translation models. These advancements are crucial for improving human-computer interaction, enabling broader access to information, and facilitating qualitative research analysis through readily available and user-friendly transcription tools.