5 papers
A Deliberation-based Joint Acoustic and Text Decoder
Sepand Mavandadi, Tara N. Sainath, Ke Hu +1
We propose a new two-pass E2E speech recognition model that improves ASR performance by training on a combination of paired data and unpaired text data. Previously, the joint acous…
Streaming End-to-End Multilingual Speech Recognition with Joint Language Identification
Chao Zhang, Bo Li, Tara Sainath +4
Language identification is critical for many downstream tasks in automatic speech recognition (ASR), and is beneficial to integrate into multilingual end-to-end ASR as an additiona…
Improving Deliberation by Text-Only and Semi-Supervised Training
Ke Hu, Tara N. Sainath, Yanzhang He +4
Text-only and semi-supervised training based on audio-only data has gained popularity recently due to the wide availability of unlabeled text and speech data. In this work, we prop…
Improving Rare Word Recognition with LM-aware MWER Training
Weiran Wang, Tongzhou Chen, Tara N. Sainath +10
Language models (LMs) significantly improve the recognition accuracy of end-to-end (E2E) models on words rarely seen during training, when used in either the shallow fusion or the…
Improving Tail Performance of a Deliberation E2E ASR Model Using a Large Text Corpus
Cal Peyser, Sepand Mavandadi, Tara N. Sainath +3
End-to-end (E2E) automatic speech recognition (ASR) systems lack the distinct language model (LM) component that characterizes traditional speech systems. While this simplifies the…