Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Shubham Toshniwal"'
Autor:
Shubham Toshniwal, Mohit Bajpai
WINBO energy method is the upgrade of old technology. This technique is created by mixing the new technology with the old technology. To make this technique, some changes were made in the wind energy method, such major changes in sources (Ox power re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b561a25b2d12d65ec5020fd83fdcfd5
Publikováno v:
ACL
We propose PeTra, a memory-augmented neural network designed to track entities in its memory slots. PeTra is trained using sparse annotation from the GAP pronoun resolution dataset and outperforms a prior memory model on the task while using a simple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b73958591c8cef40667fed6599ee9a58
https://doi.org/10.18653/v1/2020.acl-main.481
https://doi.org/10.18653/v1/2020.acl-main.481
Publikováno v:
RepL4NLP@ACL
Many natural language processing (NLP) tasks involve reasoning with textual spans, including question answering, entity recognition, and coreference resolution. While extensive research has focused on functional architectures for representing words a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c06d268048bd58c305188dd0058e15f
Autor:
Shubham Toshniwal, Tomoki Toda, Shinji Watanabe, Karen Livescu, Tomoki Hayashi, Kazuya Takeda
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7bfae55bf8db16c0d65697c7e6763e2
https://doi.org/10.21437/interspeech.2019-3177
https://doi.org/10.21437/interspeech.2019-3177
Autor:
Karen Livescu, Anjuli Kannan, Tara N. Sainath, Yonghui Wu, Chung-Cheng Chiu, Shubham Toshniwal
Publikováno v:
SLT
Attention-based recurrent neural encoder-decoder models present an elegant solution to the automatic speech recognition problem. This approach folds the acoustic model, pronunciation model, and language model into a single network and requires only a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f5e2b61b5af3a416ee45979b84e140c
https://doi.org/10.1109/slt.2018.8639038
https://doi.org/10.1109/slt.2018.8639038
Autor:
Ron Weiss, Eugene Weinstein, Kanishka Rao, Shubham Toshniwal, Bo Li, Pedro J. Moreno, Tara N. Sainath
Publikováno v:
ICASSP
Training a conventional automatic speech recognition (ASR) system to support multiple languages is challenging because the sub-word unit, lexicon and word inventories are typically language specific. In contrast, sequence-to-sequence models are well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc072842b1db4084cacc486b5a801bb5
https://doi.org/10.1109/icassp.2018.8461972
https://doi.org/10.1109/icassp.2018.8461972
Publikováno v:
NAACL-HLT
In conversational speech, the acoustic signal provides cues that help listeners disambiguate difficult parses. For automatically parsing spoken utterances, we introduce a model that integrates transcribed text and acoustic-prosodic features using a c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d46466a65ec734a5fe6e004fbbf52a96
https://doi.org/10.18653/v1/n18-1007
https://doi.org/10.18653/v1/n18-1007
Publikováno v:
INTERSPEECH
End-to-end training of deep learning-based models allows for implicit learning of intermediate representations based on the final task loss. However, the end-to-end approach ignores the useful domain knowledge encoded in explicit intermediate-level s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eeb5bce4b5fca621327d46e008f6a9ee
http://arxiv.org/abs/1704.01631
http://arxiv.org/abs/1704.01631
Autor:
Shubham Toshniwal, Karen Livescu
Publikováno v:
SLT
We propose an attention-enabled encoder-decoder model for the problem of grapheme-to-phoneme conversion. Most previous work has tackled the problem via joint sequence models that require explicit alignments for training. In contrast, the attention-en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5231222702981107e0fbb50e12605dff
Publikováno v:
IUI Companion
Audio Guides have been the prevalent mode of information delivery in public spaces such as Museums and Art Galleries. These devices are programmed to render static information to their users about the collections and artworks present and require huma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79db459f48c7ce0423a0ca991ffc48d0
https://doi.org/10.1145/2732158.2732187
https://doi.org/10.1145/2732158.2732187