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Journal ArticleDOI

Automatic spoken language identification using MFCC based time series features

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TLDR
This work proposes a model for the recognition of Indian and foreign languages, and augments data with noise of varying loudness taken from diverse environments to make the model robust to noise from everyday life.
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This article is published in Multimedia Tools and Applications.The article was published on 2022-01-03. It has received 9 citations till now. The article focuses on the topics: Computer science & Computer science.

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Journal ArticleDOI

Toward Realigning Automatic Speaker Verification in the Era of COVID-19

TL;DR: This paper examines Automatic Speaker Verification systems against the speech samples in the presence of three different types of face mask, and presents a novel framework to overcome performance degradation in these scenarios by realigning the ASV system.
Proceedings ArticleDOI

An Overview of Indian Spoken Language Recognition from Machine Learning Perspective

TL;DR: One of the very first attempts to present a comprehensive review of the Indian spoken language recognition research field is conducted, to help assess the state of the present Indian LID research by any active researcher or any research enthusiasts from related fields.
Journal ArticleDOI

The prediction model for haze pollution based on stacking framework and feature extraction of time series images.

TL;DR: Zhang et al. as discussed by the authors proposed an image-feature-stacking prediction model for univariate time series data, which converted one-dimensional time series into two-dimensional images and automatically extracted features from images, and then used a two-layer stacking ensemble learning framework to output the final predicted values.
Journal ArticleDOI

FGPat18: Feynman graph pattern-based language detection model using EEG signals

TL;DR: In this article , the authors developed an efficient handcrafted feature engineering model based on four directed graphs modeled on Feynman graph patterns (FGPat) for electroencephalography (EEG)-based language identification.
References
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Proceedings Article

Adam: A Method for Stochastic Optimization

TL;DR: This work introduces Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments, and provides a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework.
Journal ArticleDOI

The control of the false discovery rate in multiple testing under dependency

TL;DR: In this paper, it was shown that a simple FDR controlling procedure for independent test statistics can also control the false discovery rate when test statistics have positive regression dependency on each of the test statistics corresponding to the true null hypotheses.
Journal ArticleDOI

Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences

TL;DR: In this article, several parametric representations of the acoustic signal were compared with regard to word recognition performance in a syllable-oriented continuous speech recognition system, and the emphasis was on the ability to retain phonetically significant acoustic information in the face of syntactic and duration variations.
Journal ArticleDOI

Linear prediction: A tutorial review

TL;DR: This paper gives an exposition of linear prediction in the analysis of discrete signals as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal.
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