Memorias de investigación
Communications at congresses:
On the use of phone-gram units in recurrent neural networks for language identification
Year:2016
Research Areas
  • Electric engineers, electronic and automatic (eil)
Information
Abstract
In this paper we present our results on using RNN-based LM scores trained on different phone-gram orders and using different phonetic ASR recognizers. In order to avoid data sparseness problems and to reduce the vocabulary of all possible n-gram combinations, a K-means clustering procedure was performed using phone-vector embeddings as a pre-processing step. Additional experiments to optimize the amount of classes, batch-size, hidden neurons, state-unfolding, are also presented. We have worked with the KALAKA-3 database for the plenty-closed condition [1]. Thanks to our clustering technique and the combination of high level phonegrams, our phonotactic system performs ~13% better than the unigram-based RNNLM system. Also, the obtained RNNLM scores are calibrated and fused with other scores from an acoustic-based i-vector system and a traditional PPRLM system. This fusion provides additional improvements showing that they provide complementary information to the LID system.
International
Si
Congress
Odyssey 2016 - The Speaker and Language Recognition Workshop
960
Place
Bilbao - España
Reviewers
Si
ISBN/ISSN
2312-2846
Start Date
21/06/2016
End Date
24/06/2017
From page
117
To page
123
Odyssey 2016: The Speaker and Language Recognition Workshop
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