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Found 14 papers, 0 papers with code
Wavelet Scattering Transform for Improving Generalization in Low-Resourced Spoken Language Identification
We show that LID requires low octave resolution and frequency-scattering is not useful.
Cross-Corpora Spoken Language Identification with Domain Diversification and Generalization
Our experiments demonstrate that the proposed domain diversification is more promising over commonly used simple augmentation methods.
Modulation spectral features for speech emotion recognition using deep neural networks
This work explores the use of constant-Q transform based modulation spectral features (CQT-MSF) for speech emotion recognition (SER).
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
In this work, we have conducted one of the very first attempts to present a comprehensive review of the Indian spoken language recognition research field.
Analysis of constant-Q filterbank based representations for speech emotion recognition
This work analyzes the constant-Q filterbank-based time-frequency representations for speech emotion recognition (SER).
Deep scattering network for speech emotion recognition
We also investigate layer-wise scattering coefficients to analyse the importance of time shift and deformation stable scalogram and modulation spectrum coefficients for SER.
Cross-Corpora Language Recognition: A Preliminary Investigation with Indian Languages
In this paper, we conduct one of the very first studies for cross-corpora performance evaluation in the spoken language identification (LID) problem.
Non-linear frequency warping using constant-Q transformation for speech emotion recognition
In this work, we explore the constant-Q transform (CQT) for speech emotion recognition (SER).
Domain-Dependent Speaker Diarization for the Third DIHARD Challenge
This report presents the system developed by the ABSP Laboratory team for the third DIHARD speech diarization challenge.
Optimization of data-driven filterbank for automatic speaker verification
Then, we propose a new method for computing the filter frequency responses by using principal component analysis (PCA).
Quality Measures for Speaker Verification with Short Utterances
We have used the proposed quality measures as side information for combining ASV systems based on Gaussian mixture model-universal background model (GMM-UBM) and i-vector.
Novel Quality Metric for Duration Variability Compensation in Speaker Verification using i-Vectors
In experiments with the NIST SRE 2008 corpus, We have shown that inclusion of proposed quality metric exhibits considerable improvement in speaker verification performance.
Robustness of Voice Conversion Techniques Under Mismatched Conditions
Most of the existing studies on voice conversion (VC) are conducted in acoustically matched conditions between source and target signal.
Recurrent Neural Network Based Modeling of Gene Regulatory Network Using Bat Algorithm
In the next phase of this research, BA based RNN is applied to real world benchmark time series microarray dataset of E. coli.
