184 citations · 297 across the 15 of their papers we have counts for
19 papers
Large-scale Language Model Rescoring on Long-form Data
Tongzhou Chen, Cyril Allauzen, Yinghui Huang +8
In this work, we study the impact of Large-scale Language Models (LLM) on Automated Speech Recognition (ASR) of YouTube videos, which we use as a source for long-form ASR. We demon…
Alignment Entropy Regularization
Ehsan Variani, Ke Wu, David Rybach +2
Existing training criteria in automatic speech recognition(ASR) permit the model to freely explore more than one time alignments between the feature and label sequences. In this pa…
E2E Segmentation in a Two-Pass Cascaded Encoder ASR Model
W. Ronny Huang, Shuo-Yiin Chang, Tara N. Sainath +7
We explore unifying a neural segmenter with two-pass cascaded encoder ASR into a single model. A key challenge is allowing the segmenter (which runs in real-time, synchronously wit…
Global Normalization for Streaming Speech Recognition in a Modular Framework
Ehsan Variani, Ke Wu, Michael Riley +3
We introduce the Globally Normalized Autoregressive Transducer (GNAT) for addressing the label bias problem in streaming speech recognition. Our solution admits a tractable exact c…
E2E Segmenter: Joint Segmenting and Decoding for Long-Form ASR
W. Ronny Huang, Shuo-yiin Chang, David Rybach +5
Improving the performance of end-to-end ASR models on long utterances ranging from minutes to hours in length is an ongoing challenge in speech recognition. A common solution is to…
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…