no code implementations • 17 Oct 2023 • Hillary Ngai, Rohan Agrawal, Neeraj Gaur, Ronny Huang, Parisa Haghani, Pedro Moreno Mengibar
Adapters are an efficient, composable alternative to full fine-tuning of pre-trained models and help scale the deployment of large ASR models to many tasks.
no code implementations • 14 Aug 2023 • Yochai Blau, Rohan Agrawal, Lior Madmony, Gary Wang, Andrew Rosenberg, Zhehuai Chen, Zorik Gekhman, Genady Beryozkin, Parisa Haghani, Bhuvana Ramabhadran
We use text-injection to improve the recognition of PII categories by including fake textual substitutes of PII categories in the training data using a text injection method.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • 7 Aug 2023 • Chihiro Taguchi, Yusuke Sakai, Parisa Haghani, David Chiang
This paper presents a state-of-the-art model for transcribing speech in any language into the International Phonetic Alphabet (IPA).
no code implementations • 2 Mar 2023 • Yu Zhang, Wei Han, James Qin, Yongqiang Wang, Ankur Bapna, Zhehuai Chen, Nanxin Chen, Bo Li, Vera Axelrod, Gary Wang, Zhong Meng, Ke Hu, Andrew Rosenberg, Rohit Prabhavalkar, Daniel S. Park, Parisa Haghani, Jason Riesa, Ginger Perng, Hagen Soltau, Trevor Strohman, Bhuvana Ramabhadran, Tara Sainath, Pedro Moreno, Chung-Cheng Chiu, Johan Schalkwyk, Françoise Beaufays, Yonghui Wu
We introduce the Universal Speech Model (USM), a single large model that performs automatic speech recognition (ASR) across 100+ languages.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 29 Oct 2022 • Yongqiang Wang, Zhehuai Chen, Chengjian Zheng, Yu Zhang, Wei Han, Parisa Haghani
We propose a novel method to accelerate training and inference process of recurrent neural network transducer (RNN-T) based on the guidance from a co-trained connectionist temporal classification (CTC) model.
no code implementations • 13 Sep 2022 • Chao Zhang, Bo Li, Tara Sainath, Trevor Strohman, Sepand Mavandadi, Shuo-Yiin Chang, Parisa Haghani
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 additional task.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 29 Aug 2022 • Bo Li, Tara N. Sainath, Ruoming Pang, Shuo-Yiin Chang, Qiumin Xu, Trevor Strohman, Vince Chen, Qiao Liang, Heguang Liu, Yanzhang He, Parisa Haghani, Sameer Bidichandani
On-device end-to-end (E2E) models have shown improvements over a conventional model on English Voice Search tasks in both quality and latency.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 5 Apr 2022 • Zhiyun Lu, Yongqiang Wang, Yu Zhang, Wei Han, Zhehuai Chen, Parisa Haghani
Self-supervised learning of speech representations has achieved impressive results in improving automatic speech recognition (ASR).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 8 Oct 2021 • Zhiyun Lu, Yanwei Pan, Thibault Doutre, Parisa Haghani, Liangliang Cao, Rohit Prabhavalkar, Chao Zhang, Trevor Strohman
Our experiments show that for both losses, the WER on long-form speech reduces substantially as the training utterance length increases.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 30 Apr 2021 • Bo Li, Ruoming Pang, Tara N. Sainath, Anmol Gulati, Yu Zhang, James Qin, Parisa Haghani, W. Ronny Huang, Min Ma, Junwen Bai
Building ASR models across many languages is a challenging multi-task learning problem due to large variations and heavily unbalanced data.
2 code implementations • 21 Feb 2019 • Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia X. Chen, Ye Jia, Anjuli Kannan, Tara Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel A. U. Bacchiani, Thomas B. Jablin, Rob Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon
Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models.
no code implementations • 24 Sep 2018 • Parisa Haghani, Arun Narayanan, Michiel Bacchiani, Galen Chuang, Neeraj Gaur, Pedro Moreno, Rohit Prabhavalkar, Zhongdi Qu, Austin Waters
Conventional spoken language understanding systems consist of two main components: an automatic speech recognition module that converts audio to a transcript, and a natural language understanding module that transforms the resulting text (or top N hypotheses) into a set of domains, intents, and arguments.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • 16 Aug 2018 • Arun Narayanan, Ananya Misra, Khe Chai Sim, Golan Pundak, Anshuman Tripathi, Mohamed Elfeky, Parisa Haghani, Trevor Strohman, Michiel Bacchiani
More importantly, such models generalize better to unseen conditions and allow for rapid adaptation -- we show that by using as little as 10 hours of data from a new domain, an adapted domain-invariant model can match performance of a domain-specific model trained from scratch using 70 times as much data.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1