Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Jain, Mahaveer"'
Autor:
Le, Duc, Jain, Mahaveer, Keren, Gil, Kim, Suyoun, Shi, Yangyang, Mahadeokar, Jay, Chan, Julian, Shangguan, Yuan, Fuegen, Christian, Kalinli, Ozlem, Saraf, Yatharth, Seltzer, Michael L.
How to leverage dynamic contextual information in end-to-end speech recognition has remained an active research area. Previous solutions to this problem were either designed for specialized use cases that did not generalize well to open-domain scenar
Externí odkaz:
http://arxiv.org/abs/2104.02194
Autor:
Jain, Mahaveer, Keren, Gil, Mahadeokar, Jay, Zweig, Geoffrey, Metze, Florian, Saraf, Yatharth
End-to-end (E2E) systems for automatic speech recognition (ASR), such as RNN Transducer (RNN-T) and Listen-Attend-Spell (LAS) blend the individual components of a traditional hybrid ASR system - acoustic model, language model, pronunciation model - i
Externí odkaz:
http://arxiv.org/abs/2006.03411
As one of the major sources in speech variability, accents have posed a grand challenge to the robustness of speech recognition systems. In this paper, our goal is to build a unified end-to-end speech recognition system that generalizes well across a
Externí odkaz:
http://arxiv.org/abs/1911.11935
Autor:
Jain, Mahaveer, Schubert, Kjell, Mahadeokar, Jay, Yeh, Ching-Feng, Kalgaonkar, Kaustubh, Sriram, Anuroop, Fuegen, Christian, Seltzer, Michael L.
Neural transducer-based systems such as RNN Transducers (RNN-T) for automatic speech recognition (ASR) blend the individual components of a traditional hybrid ASR systems (acoustic model, language model, punctuation model, inverse text normalization)
Externí odkaz:
http://arxiv.org/abs/1911.01629
Autor:
Yeh, Ching-Feng, Mahadeokar, Jay, Kalgaonkar, Kaustubh, Wang, Yongqiang, Le, Duc, Jain, Mahaveer, Schubert, Kjell, Fuegen, Christian, Seltzer, Michael L.
We explore options to use Transformer networks in neural transducer for end-to-end speech recognition. Transformer networks use self-attention for sequence modeling and comes with advantages in parallel computation and capturing contexts. We propose
Externí odkaz:
http://arxiv.org/abs/1910.12977
End-to-end modeling (E2E) of automatic speech recognition (ASR) blends all the components of a traditional speech recognition system into a unified model. Although it simplifies training and decoding pipelines, the unified model is hard to adapt when
Externí odkaz:
http://arxiv.org/abs/1812.02142
Publikováno v:
In Measurement December 2019 148
Publikováno v:
In Materials Science & Engineering B January 2015 191:7-14
Publikováno v:
In Applied Surface Science 2011 258(5):1744-1749
Publikováno v:
In Applied Surface Science 2011 257(20):8623-8628