Feature extraction methods in language identification: a survey

D Deshwal, P Sangwan, D Kumar - Wireless Personal Communications, 2019 - Springer
Abstract Language Identification (LI) is one of the widely emerging field in the areas of
speech processing to accurately identify the language from the data base based on some …

Text-independent speaker verification based on triplet convolutional neural network embeddings

C Zhang, K Koishida… - IEEE/ACM Transactions on …, 2018 - ieeexplore.ieee.org
The effectiveness of introducing deep neural networks into conventional speaker recognition
pipelines has been broadly shown to benefit system performance. A novel text-independent …

Dialogue system incorporating unique speech to text conversion method for meaningful dialogue response

NK Goel, M Sarma - US Patent 10,347,244, 2019 - Google Patents
A real-time dialogue system that provides real-time transcription of the spoken text, with a
sub-second delay by keeping track of word timings and word accuracy is provided. The …

An overview of Indian spoken language recognition from machine learning perspective

S Dey, M Sahidullah, G Saha - ACM Transactions on Asian and Low …, 2022 - dl.acm.org
Automatic spoken language identification (LID) is a very important research field in the era of
multilingual voice-command-based human-computer interaction. A front-end LID module …

Advances in deep neural network approaches to speaker recognition

M McLaren, Y Lei, L Ferrer - 2015 IEEE international …, 2015 - ieeexplore.ieee.org
The recent application of deep neural networks (DNN) to speaker identification (SID) has
resulted in significant improvements over current state-of-the-art on telephone speech. In …

Short utterance based speech language identification in intelligent vehicles with time-scale modifications and deep bottleneck features

Z Ma, H Yu, W Chen, J Guo - IEEE transactions on vehicular …, 2018 - ieeexplore.ieee.org
Conversations in the intelligent vehicles are usually short utterance. As the durations of the
short utterances are small (eg, less than 3 s), it is difficult to learn sufficient information to …

Multilingually trained bottleneck features in spoken language recognition

R Fer, P Matějka, F Grézl, O Plchot, K Veselý… - Computer Speech & …, 2017 - Elsevier
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 …

An analysis of the influence of deep neural network (DNN) topology in bottleneck feature based language recognition

A Lozano-Diez, R Zazo, DT Toledano… - PloS one, 2017 - journals.plos.org
Language recognition systems based on bottleneck features have recently become the state-
of-the-art in this research field, showing its success in the last Language Recognition …

A deep dive into deep learning techniques for solving spoken language identification problems

HS Das, P Roy - Intelligent speech signal processing, 2019 - Elsevier
Automatic language identification has always been a challenging issue and an important
research area in speech signal processing. It is the process of identifying a language from a …

Phonetic temporal neural model for language identification

Z Tang, D Wang, Y Chen, L Li… - IEEE/ACM Transactions …, 2017 - ieeexplore.ieee.org
Deep neural models, particularly the long short-term memory recurrent neural network
(LSTM-RNN) model, have shown great potential for language identification (LID). However …