Add to ORKGThis work explores the use of Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) for automatic lan-guage identification (LID). The use of RNNs is motivated by their better ability in modeling sequences with respect to feed forward networks used in previous works. We show that LSTM RNNs can effectively exploit temporal dependencies in acoustic data, learning relevant features for language discrimination pur-poses. The proposed approach is compared to baseline i-vector and feed forward Deep Neural Network (DNN) systems in the NIST Language Recognition Evaluation 2009 dataset. We show LSTM RNNs achieve better performance than our best DNN system with an order of magnitude fewer parameters. Further, the combination of the different ...
Applying Artificial Neural Networks (ANNs) to language learning has been an active area of research ...
Long short-term memory (LSTM) recurrent neural networks (RNNs) have been shown to give state-of-the-...
Ebru Arısoy (MEF Author)##nofulltext##Recurrent neural network language models have enjoyed great su...
Automatic language identification (LID) belongs to the automatic process whereby the identity of the...
Deep neural models, particularly the long short-term memory recurrent neural network (LSTM-RNN) mode...
Long Short-Term Memory (LSTM) is a recurrent neural network (RNN) architecture that has been designe...
Language identification is the task of identifying the language of the spoken utterance. Deep neural...
AbstractIn this work, we present a comprehensive study on the use of deep neural networks (DNNs) for...
Zazo R, Lozano-Diez A, Gonzalez-Dominguez J, T. Toledano D, Gonzalez-Rodriguez J (2016) Language Ide...
This work studies the use of deep neural networks (DNNs) to address automatic language identificatio...
Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training metho...
Long short-term memory (LSTM) recurrent neural networks (RNNs) have been shown to give state-of-the-...
Speaker adaptation of deep neural networks (DNNs) based acoustic models is still a challenging area ...
Speaker adaptation of deep neural networks (DNNs) based acoustic models is still a challenging area ...
This work addresses the use of deep neural networks (DNNs) in automatic language identification (LID...
Applying Artificial Neural Networks (ANNs) to language learning has been an active area of research ...
Long short-term memory (LSTM) recurrent neural networks (RNNs) have been shown to give state-of-the-...
Ebru Arısoy (MEF Author)##nofulltext##Recurrent neural network language models have enjoyed great su...
Automatic language identification (LID) belongs to the automatic process whereby the identity of the...
Deep neural models, particularly the long short-term memory recurrent neural network (LSTM-RNN) mode...
Long Short-Term Memory (LSTM) is a recurrent neural network (RNN) architecture that has been designe...
Language identification is the task of identifying the language of the spoken utterance. Deep neural...
AbstractIn this work, we present a comprehensive study on the use of deep neural networks (DNNs) for...
Zazo R, Lozano-Diez A, Gonzalez-Dominguez J, T. Toledano D, Gonzalez-Rodriguez J (2016) Language Ide...
This work studies the use of deep neural networks (DNNs) to address automatic language identificatio...
Recurrent neural networks (RNNs) are a powerful model for sequential data. End-to-end training metho...
Long short-term memory (LSTM) recurrent neural networks (RNNs) have been shown to give state-of-the-...
Speaker adaptation of deep neural networks (DNNs) based acoustic models is still a challenging area ...
Speaker adaptation of deep neural networks (DNNs) based acoustic models is still a challenging area ...
This work addresses the use of deep neural networks (DNNs) in automatic language identification (LID...
Applying Artificial Neural Networks (ANNs) to language learning has been an active area of research ...
Long short-term memory (LSTM) recurrent neural networks (RNNs) have been shown to give state-of-the-...
Ebru Arısoy (MEF Author)##nofulltext##Recurrent neural network language models have enjoyed great su...