Results 41 to 50 of about 2,597,894 (294)

Emotion Recognition from Speech

CoRR, 2019
In this work, we conduct an extensive comparison of various approaches to speech based emotion recognition systems. The analyses were carried out on audio recordings from Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). After pre-processing the raw audio files, features such as Log-Mel Spectrogram, Mel-Frequency Cepstral ...
Kannan Venkataramanan, Haresh Rengaraj Rajamohan   +1 more
openaire   +2 more sources

Speech Emotion Recognition Based on Voice Rhythm Differences [PDF]

Jisuanji kexue
Speech emotion recognition has an important application prospect in financial anti-fraud and other fields,but it is increasingly difficult to improve the accuracy of speech emotion recognition.The existing methods of speech emotion recognition based on ...
ZHANG Jiahao, ZHANG Zhaohui, YAN Qi, WANG Pengwei
doaj   +1 more source

The Automatic Recognition of Emotions in Speech [PDF]

, 2010
In this chapter, we focus on the automatic recognition of emotional states using acoustic and linguistic parameters as features and classifiers as tools to predict the ‘correct’ emotional states. We first sketch history and state of the art in this field; then we describe the process of ‘corpus engineering’, i.e.
Anton Batliner, Björn Schuller, Dino Seppi, Stefan Steidl, Laurence Devillers, Laurence Vidrascu, Thurid Vogt, Vered Aharonson, Noam Amir   +8 more
openaire   +2 more sources

A multimodal approach to emotion recognition ability in autism spectrum disorders [PDF]

, 2010
Background:  Autism spectrum disorders (ASD) are characterised by social and communication difficulties in day‐to‐day life, including problems in recognising emotions.
Tregay, Jeni, Charman, Tony; id_orcid, Jones, Catherine RG, Rebecca J. Phillips, Catherine R.G. Jones, Sauter, Disa, Charman, Tony, Scott, SK, Happé, Francesca, Jones, Catherine, Simonoff, Emily; id_orcid, Pickles, A, Marsden, Anita J.S., Phillips, Rebecca J., Happé, F., Sauter, D.; id_orcid, Salter, Disa, Scott, S.K., Marsden, Anita, Emily Simonoff, Andrew Pickles, Marsden, A.J.S., Happe, F, Simonoff, Emily, Phillips, R.J., Pickles, A., Phillips, Rebecca J, Jones, CRG, Tregay, J, Jones, Catherine R.G., Falcaro, M., Falcaro, M, Baird, Gillian, Milena Falcaro, Scott, Sophie K, Tregay, Jenifer, Falcaro, Milena, Scott, Sophie, Marsden, Anita JS, Jones, C., Marsden, A., Baird, G., Phillips, R., Jones, C.R.G., Marsden, Anita J. S., Marsden, AJS, Charman, T, Baird, G, Tregay, J., Jones, Catherine R. G., Sophie K. Scott, Disa Sauter, Scott, Sophie K., Charman, T., Sauter, D, Anita J.S. Marsden, Tony Charman, Scott, S., Pickles, Andrew, Phillips, Rebecca, Francesca Happé, Sauter, D., Jenifer Tregay, Gillian Baird, Simonoff, E, Phillips, RJ, Simonoff, E.   +66 more
core   +2 more sources

A Hybrid Speech Emotion Recognition System Based on Spectral and Prosodic Features [PDF]

, 2010
In this paper, we present a hybrid speech emotion recognition system exploiting both spectral and prosodic features in speech. For capturing the emotional information in the spectral domain, we propose a new spectral feature extraction method by applying
Yanqing SUN, SUN, Yanqing, Yonghong YAN, Yu ZHOU, Masato AKAGI, Junfeng LI, YAN, Yonghong, AKAGI, Masato, LI, Junfeng, ZHOU, Yu, ZHANG, Jianping, Jianping ZHANG   +11 more
core   +1 more source

Continual Disentanglement Generation for Speech Emotion Recognition [PDF]

Jisuanji kexue yu tansuo
A continual disentanglement generation for speech emotion recognition is proposed to address the problems of the lack of large amounts of labeled training data for speech models and the inability of speech models to learn incrementally in the field of ...
NING Meiling, QI Jiayin, LIANG Kuai, ZHANG Xun, CHEN Kaifan
doaj   +1 more source

Artificial Neural Network vs. Support Vector Machine For Speech Emotion Recognition

Tikrit Journal of Pure Science, 2023
Today, the subject of emotion recognition from speech got the attention of many researchers who are interested in the topic of speech recognition and it has engaged in many applications.
Mohamed. A. Ahmad
doaj   +1 more source

Poster Abstract: Federated Learning for Speech Emotion Recognition Applications

, 2020
Privacy concerns are considered one of the major challenges in the applications of speech emotion recognition (SER) as it involves the complete sharing of speech data, which can bring threatening consequences to people’s lives.
Raja Jurdak, Siddique Latif, Latif, Siddique, Rana, Rajib, Sara Khalifa, Khalifa, Sara, Jurdak, Raja, Rajib Rana   +7 more
core   +1 more source

Speech Emotion Recognition Using an Enhanced Kernel Isomap for Human-Robot Interaction

International Journal of Advanced Robotic Systems, 2013
Speech emotion recognition is currently an active research subject and has attracted extensive interest in the science community due to its vital application to human-robot interaction.
Shiqing Zhang, Xiaoming Zhao, Bicheng Lei   +2 more
doaj   +1 more source

Speech Emotion Recognition Based on Selective Interpolation Synthetic Minority Over-Sampling Technique in Small Sample Environment

Sensors, 2020
Speech emotion recognition often encounters the problems of data imbalance and redundant features in different application scenarios. Researchers usually design different recognition models for different sample conditions. In this study, a speech emotion
Zhen-Tao Liu, Bao-Han Wu, Dan-Yun Li, Peng Xiao, Jun-Wei Mao   +4 more
doaj   +1 more source