no code implementations • 23 Jan 2024 • W. Ronny Huang, Cyril Allauzen, Tongzhou Chen, Kilol Gupta, Ke Hu, James Qin, Yu Zhang, Yongqiang Wang, Shuo-Yiin Chang, Tara N. Sainath
In the era of large models, the autoregressive nature of decoding often results in latency serving as a significant bottleneck.
no code implementations • 13 Jun 2023 • Tongzhou Chen, Cyril Allauzen, Yinghui Huang, Daniel Park, David Rybach, W. Ronny Huang, Rodrigo Cabrera, Kartik Audhkhasi, Bhuvana Ramabhadran, Pedro J. Moreno, Michael Riley
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.
no code implementations • 22 Dec 2022 • Ehsan Variani, Ke wu, David Rybach, Cyril Allauzen, Michael Riley
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.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
no code implementations • 28 Nov 2022 • W. Ronny Huang, Shuo-Yiin Chang, Tara N. Sainath, Yanzhang He, David Rybach, Robert David, Rohit Prabhavalkar, Cyril Allauzen, Cal Peyser, Trevor D. Strohman
We explore unifying a neural segmenter with two-pass cascaded encoder ASR into a single model.
1 code implementation • 26 May 2022 • Ehsan Variani, Ke wu, Michael Riley, David Rybach, Matt Shannon, Cyril Allauzen
We introduce the Globally Normalized Autoregressive Transducer (GNAT) for addressing the label bias problem in streaming speech recognition.
no code implementations • 22 Apr 2022 • W. Ronny Huang, Shuo-Yiin Chang, David Rybach, Rohit Prabhavalkar, Tara N. Sainath, Cyril Allauzen, Cal Peyser, Zhiyun Lu
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.
no code implementations • 14 Apr 2022 • Kyle Gorman, Cyril Allauzen
We describe an algorithm which finds the shortest string for a weighted non-deterministic automaton over such semirings using the backwards shortest distance of an equivalent deterministic automaton (DFA) as a heuristic for A* search performed over a companion idempotent semiring, which is proven to return the shortest string.
no code implementations • 12 Mar 2020 • Ehsan Variani, David Rybach, Cyril Allauzen, Michael Riley
This paper proposes and evaluates the hybrid autoregressive transducer (HAT) model, a time-synchronous encoderdecoder model that preserves the modularity of conventional automatic speech recognition systems.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
no code implementations • CONLL 2019 • Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Françoise Beaufays, Michael Riley
The n-gram language models trained with federated learning are compared to n-grams trained with traditional server-based algorithms using A/B tests on tens of millions of users of virtual keyboard.
no code implementations • WS 2019 • Marco Cognetta, Cyril Allauzen, Michael Riley
Indeed, a delicate balance between comprehensiveness, speed, and memory must be struck to conform to device requirements while providing a good user experience. In this paper, we describe a compression scheme for lexicons when represented as finite-state transducers.