Publication detail

Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model

DEORAS, A. MIKOLOV, T. KOMBRINK, S. CHURCH, K.

Original Title

Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model

English Title

Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model

Type

journal article in Web of Science

Language

en

Original Abstract

This paper deals with approximate inference: a sampling based modeling technique to capture complex dependencies in a language model

English abstract

This paper deals with approximate inference: a sampling based modeling technique to capture complex dependencies in a language model

Keywords

Long-span language models; Recurrent neural networks; Speech recognition; Decoding

RIV year

2012

Released

21.08.2012

Publisher

Elsevier Science

Location

NEUVEDEN

ISBN

0167-6393

Periodical

Speech Communication

Year of study

2012

Number

8

State

NL

Pages from

1

Pages to

16

Pages count

16

URL

Documents

BibTex


@article{BUT97047,
  author="Anoop {Deoras} and Tomáš {Mikolov} and Stefan {Kombrink} and Kenneth {Church}",
  title="Approximate inference: A sampling based modeling technique to capture complex dependencies in a language model",
  annote="This paper deals with approximate inference: a sampling based modeling technique
to capture complex dependencies in a language model",
  address="Elsevier Science",
  booktitle="Speech Communication",
  chapter="97047",
  doi="10.1016/j.specom.2012.08.004",
  edition="NEUVEDEN",
  howpublished="print",
  institution="Elsevier Science",
  number="8",
  volume="2012",
  year="2012",
  month="august",
  pages="1--16",
  publisher="Elsevier Science",
  type="journal article in Web of Science"
}