Improving Large-scale Deep Biasing with Phoneme Features and Text-only Data in Streaming Transducer
Journal: arXiv (Cornell University)
Year: 2023

Deep biasing for the Transducer can improve the recognition performance of rare words or contextual entities, which is essential in practical applications, especially for streaming Automatic Speech Recognition (ASR). However, deep biasing with large-scale rare words remains challenging, as the performance drops significantly when more distractors exist and there are words with similar grapheme sequences in the bias list. In this paper, we combine the phoneme and textual information of rare words