RNN T Loss

RNN-T loss is a crucial component of recurrent neural network transducers (RNN-Ts), a popular architecture for automatic speech recognition (ASR). Current research focuses on improving RNN-T's efficiency and accuracy, exploring alternative architectures like CIF-T to reduce computational overhead and enhance the predictor network's role, and developing more flexible frameworks for loss function modification. These advancements aim to improve ASR performance, particularly in low-resource scenarios and for large vocabularies, leading to more accurate and efficient speech recognition systems across various languages and applications.