The determination and classification of a recognized spoken language based on certain
contents and datasets is known as the process of language identification (LID). The common …

Natural language classification and determination based on a particular content and dataset
is carried out using Spoken Language Identification (LID) which typically involves the …

Multilingual training of neural networks has proven to be simple yet effective way to deal with
multilingual training corpora. It allows to use several resources to jointly train a language …

This paper compares different approaches for using deep neural networks (DNNs) trained to
predict senone posteriors for the task of spoken language recognition (SLR). These …

In this paper, we aim to improve traditional DNN x-vector language identification (LID)
performance by employing Convolutional and Long Short Term Memory-Recurrent (CLSTM) …

In this work, we present a comprehensive study on the use of deep neural networks (DNNs)
for automatic language identification (LID). Motivated by the recent success of using DNNs …

The determination and classification of natural language based on specified content and
data set involves a process known as spoken language identification (LID). To initiate the …

In this paper, we investigate Multilingual Stacked Bottleneck Features (SBN) in language
recognition domain. These features are extracted using bottleneck neural networks trained …

Acoustic scene classification (ASC) using front-end timefrequency features and back-end
neural network classifiers has demonstrated good performance in recent years. However a …

Emotion recognition plays an important role in human-computer interaction. Previously and
currently, many studies focused on speech emotion recognition using several classifiers and …