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20172025
most citedModulation spectral features for speech emotion recognition using deep neural networks

72 citations · 174 across the 17 of their papers we have counts for

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Showing 2021 · eess.ASShow all

6 papers · 2 filters

eess.AS2021

ASVspoof 2021: accelerating progress in spoofed and deepfake speech detection

Junichi Yamagishi, Xin Wang, Massimiliano Todisco +8

ASVspoof 2021 is the forth edition in the series of bi-annual challenges which aim to promote the study of spoofing and the design of countermeasures to protect automatic speaker v…

eess.AS2021

StutterNet: Stuttering Detection Using Time Delay Neural Network

Shakeel A. Sheikh, Md Sahidullah, Fabrice Hirsch +1

This paper introduces StutterNet, a novel deep learning based stuttering detection capable of detecting and identifying various types of disfluencies. Most of the existing work in…

eess.AS2021

Cross-Corpora Language Recognition: A Preliminary Investigation with Indian Languages

Spandan Dey, Goutam Saha, Md Sahidullah

In this paper, we conduct one of the very first studies for cross-corpora performance evaluation in the spoken language identification (LID) problem. Cross-corpora evaluation was n…

eess.AS2021

Deep scattering network for speech emotion recognition

Premjeet Singh, Goutam Saha, Md Sahidullah

This paper introduces scattering transform for speech emotion recognition (SER). Scattering transform generates feature representations which remain stable to deformations and shif…

eess.AS2021

ABSP System for The Third DIHARD Challenge

A Kishore Kumar, Shefali Waldekar, Goutam Saha +1

This report describes the speaker diarization system developed by the ABSP Laboratory team for the third DIHARD speech diarization challenge. Our primary contribution is to develop…

eess.AS2021

Non-linear frequency warping using constant-Q transformation for speech emotion recognition

Premjeet Singh, Goutam Saha, Md Sahidullah

In this work, we explore the constant-Q transform (CQT) for speech emotion recognition (SER). The CQT-based time-frequency analysis provides variable spectro-temporal resolution wi…