New Feature Vectors for Language Identification Using Deep Neural Networks

A. Nagesh


The impressive performance of neural networks (NNs) for automatic speech recognition has motivated us to use for language identification (LID). In this paper, a new features based language identification system using neural network is presented. The new feature vectors are extracted based on the principle the frequency of occurrence phonemes is different among the languages. In this new form of feature vectors, the feature vectors are represented as a probability vector instead of scalar value. Because of this these new form of feature vectors, the DNN classifier classify the languages under consideration accurately.

Full Text:



R.A. Cole, J.W.T. Inouye, Y.K. Muthusamy, and M. Gopalakrishnan, Language identification with neural networks: a feasibility study, in Communications, Computers and Signal Processing, 1989. Conference Proceeding.,

M. Leena, K. Srinivasa Rao, and B. Yegnanarayana, Neural network classifiers for language identification using phonotactic and prosodic features, in Intelligent Sensing and Information Processing, 2005.

D. Yu and L. Deng, “Deep Learning and its Applications to Signal and Information Processing, IEEE, vol. 28, no. 1, pp. 145–154, 2011.

N. Jaitly, P. Nguyen, A. Senior, and V. Vanhoucke, Application of Pretrained Deep Neural Networks to Large Vocabulary speech recognition, in Proceedings of Interspeech 2012.

Richardson, F., Reynolds, D., Dehak, N., 2015. A Unified Deep Neural Network for Speaker and Language Recognition

McCree, A., Multiclass discriminative training of i-vector language recognition. In: IEEE Odyssey: The Speaker and Language Recognition Workshop. Joensu, Finland, 2014.

G. Hinton, L. Deng, D. Yu, G.E. Dahl, A. Mohamed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T.N. Sainath, and B. Kingsbury, “Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups,” Signal Processing Magazine, IEEE, vol. 29, no. 6, pp. 82–97, 2012.

Y. Lei, L. Ferrer, A. Lawson, M. McLaren, and N. Scheffer, “Application of convolutional neural networks to language identification in noisy conditions,” in Proc. Odyssey-14, Joensuu, Finland, June 2014.

I. Lopez-Moreno, J. Gonzalez-Dominguez, O. Plchot, D. MartınezGonzalez, J. Gonzalez-Rodriguez, and PJ Moreno, “Automatic language identification using deep neural networks,” in Proc. ICASSP, Florence, Italy, May 2014.

Desai S, Black A W, Yegnanarayana B, Prahlad K 2010 Spectral mapping using artificial neural networks for voice conversion. IEEE Trans. Audio Speech Lang. Process. 18(5): 954–964.



  • There are currently no refbacks.