Spoken language recognition based on senone posteriors

@inproceedings{Ferrer2014SpokenLR,
  title={Spoken language recognition based on senone posteriors},
  author={Luciana Ferrer and Yun Lei and Mitchell McLaren and Nicolas Scheffer},
  booktitle={INTERSPEECH},
  year={2014}
}
This paper explores in depth a recently proposed approach to spoken language recognition based on the estimated posteriors for a set of senones representing the phonetic space of one or more languages. A neural network (NN) is trained to estimate the posterior probabilities for the senones at a frame level. A feature vector is then derived for every sample using these posteriors. The effect of the language used in training the NN and the number of senones are studied. Speech-activity detection… CONTINUE READING

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