Speech emotion recognition from spectrograms with deep convolutional neural network
This paper presents a method for speech emotion recognition using spectrograms and deep
convolutional neural network (CNN). Spectrograms generated from the speech signals are …
convolutional neural network (CNN). Spectrograms generated from the speech signals are …
Paralinguistics in speech and language—state-of-the-art and the challenge
Paralinguistic analysis is increasingly turning into a mainstream topic in speech and
language processing. This article aims to provide a broad overview of the constantly …
language processing. This article aims to provide a broad overview of the constantly …
Affective and behavioural computing: Lessons learnt from the first computational paralinguistics challenge
In this article, we review the INTERSPEECH 2013 Computational Paralinguistics ChallengE
(ComParE)–the first of its kind–in light of the recent developments in affective and …
(ComParE)–the first of its kind–in light of the recent developments in affective and …
Improving on-device speaker verification using federated learning with privacy
Information on speaker characteristics can be useful as side information in improving
speaker recognition accuracy. However, such information is often private. This paper …
speaker recognition accuracy. However, such information is often private. This paper …
Automatic speaker age and gender recognition using acoustic and prosodic level information fusion
The paper presents a novel automatic speaker age and gender identification approach
which combines seven different methods at both acoustic and prosodic levels to improve the …
which combines seven different methods at both acoustic and prosodic levels to improve the …
Machine-learning analysis of voice samples recorded through smartphones: the combined effect of ageing and gender
Background: Experimental studies using qualitative or quantitative analysis have
demonstrated that the human voice progressively worsens with ageing. These studies …
demonstrated that the human voice progressively worsens with ageing. These studies …
Speaker dependent speech emotion recognition using MFCC and Support Vector Machine
PP Dahake, K Shaw, P Malathi - … International Conference on …, 2016 - ieeexplore.ieee.org
In human computer interaction, speech emotion recognition is playing a pivotal part in the
field of research. Human emotions consist of being angry, happy, sad, disgust, neutral. In …
field of research. Human emotions consist of being angry, happy, sad, disgust, neutral. In …
Demographic analysis from biometric data: Achievements, challenges, and new frontiers
Biometrics is the technique of automatically recognizing individuals based on their biological
or behavioral characteristics. Various biometric traits have been introduced and widely …
or behavioral characteristics. Various biometric traits have been introduced and widely …
Deep and shallow features fusion based on deep convolutional neural network for speech emotion recognition
L Sun, J Chen, K **e, T Gu - International Journal of Speech Technology, 2018 - Springer
Recent years have witnessed the great progress for speech emotion recognition using deep
convolutional neural networks (DCNNs). In order to improve the performance of speech …
convolutional neural networks (DCNNs). In order to improve the performance of speech …
[PDF][PDF] Automatic identification of gender from speech
Identifying the gender of a speaker from speech has a variety of applications ranging from
speech analytics to personalizing human-machine interactions. While gender identification …
speech analytics to personalizing human-machine interactions. While gender identification …