Memorias de investigación
Research Publications in journals:
Language Recognition Using Neural Phone Embeddings and RNNLMs
Year:2018

Research Areas
  • Electric engineers, electronic and automatic (eil)

Information
Abstract
New advances in Language Identification (LID) using Recurrent Neural Networks (RNNs) and Neural Embeddings have been proposed recently. While their application has been successfully applied at a word level, results at a phoneme level may not be as good because of the greater variability found in phoneme sequences which reduces LID accuracy. Thus, we propose to use phonetic units called ?phone-grams? that implicitly include longer-context information and use them to train neural embeddings and RNN language models (RNNLMs). Neural embeddings are used in a pre-processing data phase to reduce the scattering problem produced by the high number of resulting phone-gram units, and, in a second phase, we have used the RNNLMs to obtain the scores of each language in the identification task following a PPRLM structure. Results in terms of Cavg on the KALAKA-3 database show that the use of phone-grams provides up to 14.4% relative improvement over a baseline using only phonemes as features. In addition, our proposed strategy of reducing the number of phone-gram units using neural embeddings contributes to obtain up to 23.0% relative improvement. Finally, fusing the best system with MFCC-based acoustic i-vectors and a traditional PPRLM architecture provides up to 39.3% improvement.
International
Si
JCR
Si
Title
Ieee Latin America Transactions
ISBN
1548-0992
Impact factor JCR
0,631
Impact info
Datos JCR del año 2016
Volume
Journal number
From page
1
To page
8
Month
SIN MES
Ranking
Participants

Research Group, Departaments and Institutes related
  • Creador: Centro o Instituto I+D+i: Centro de I+d+i en Procesado de la Información y Telecomunicaciones
  • Departamento: Ingeniería Electrónica