Publication result detail

Strategies for Training Large Scale Neural Network Language Models

MIKOLOV, T.; DEORAS, A.; POVEY, D.; BURGET, L.; ČERNOCKÝ, J.

Original Title

Strategies for Training Large Scale Neural Network Language Models

English Title

Strategies for Training Large Scale Neural Network Language Models

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

Techniques for effective training of recurrent neural network based language models are described, and new state-of-the-art results on standard speech recognition task are reported.

English abstract

Techniques for effective training of recurrent neural network based language models are described, and new state-of-the-art results on standard speech recognition task are reported.

Keywords

recurrent neural network, language model, speech recognition, maximum entropy

Key words in English

recurrent neural network, language model, speech recognition, maximum entropy

Authors

MIKOLOV, T.; DEORAS, A.; POVEY, D.; BURGET, L.; ČERNOCKÝ, J.

RIV year

2012

Released

11.12.2011

Publisher

IEEE Signal Processing Society

Location

Hilton Waikoloa Village, Big Island, Hawaii

ISBN

978-1-4673-0366-8

Book

Proceedings of ASRU 2011

Pages from

196

Pages to

201

Pages count

6

URL

BibTex

@inproceedings{BUT76453,
  author="Tomáš {Mikolov} and Anoop {Deoras} and Daniel {Povey} and Lukáš {Burget} and Jan {Černocký}",
  title="Strategies for Training Large Scale Neural Network Language Models",
  booktitle="Proceedings of ASRU 2011",
  year="2011",
  pages="196--201",
  publisher="IEEE Signal Processing Society",
  address="Hilton Waikoloa Village, Big Island, Hawaii",
  isbn="978-1-4673-0366-8",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2011/mikolov_asru2011_00196.pdf"
}