Speech emotion recognition of Hindi speech using statistical and machine learning techniques

被引：6

作者：

Agrawal, Akshat ^{[1
]}

Jain, Anurag ^{[1
]}

机构：

[1] Guru Gobind Singh Indraprastha Univ, Univ Sch Informat Commun & Technol, Sect 16C, New Delhi 110078, India

来源：

JOURNAL OF INTERDISCIPLINARY MATHEMATICS | 2020年 / 23卷 / 01期

关键词：

Speech Emotion Recognition; Statistical approach; KNN; Naive Bayes; Prosodic features; CLASSIFICATION; FEATURES;

D O I：

10.1080/09720502.2020.1721926

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Now a days speech is fastest medium of giving instruction to machines to do any task. When a person uttered a word at that time machine can understand the semantic of the utterance but not the emotion related with that utterance. This study mainly focused on combining on different types of speech features together and then this paper used various statistical techniques for reducing the dimensionality of data and then applying machine learning algorithm to train dataset and predicting the emotional state of the person so that while receiving the instruction form humans, machines can provide better response for recognizing emotion.

引用

页码：311 / 319

页数：9

共 50 条

[41] APPLICATION OF STATISTICAL TECHNIQUES TO SPEECH RECOGNITION
BERGERVACHON, C
AUTOMATISME, 1972, 17 (03): : 76 - +
[42] Deep Learning, Ensemble and Supervised Machine Learning for Arabic Speech Emotion Recognition
Ismaiel, Wahiba
Alhalangy, Abdalilah
Mohamed, Adil. O. Y.
Musa, Abdalla Ibrahim Abdalla
ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH, 2024, 14 (02) : 13757 - 13764
[43] Comparative Wavelet, PLP and LPC Speech Recognition Techniques on the Hindi Speech Digits Database
Mishra, A. N.
Shrotriya, M. C.
Sharan, S. N.
SECOND INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING, 2010, 7546
[44] Exploring Speech Emotion Recognition in Tribal Language with Deep Learning Techniques
Nayak, Subrat Kumar
Nayak, Ajit Kumar
Mishra, Smitaprava
Mohanty, Prithviraj
Tripathy, Nrusingha
Chaudhury, Kumar Surjeet
INTERNATIONAL JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING SYSTEMS, 2025, 16 (01) : 53 - 64
[45] Deep Learning Techniques for Speech Emotion Recognition, from Databases to Models
Abbaschian, Babak Joze
Sierra-Sosa, Daniel
Elmaghraby, Adel
SENSORS, 2021, 21 (04) : 1 - 27
[46] Machine Learning Approaches for Speech Emotion Recognition: Classic and Novel Advances
Heracleous, Panikos
Ishikawa, Akio
Yasuda, Keiji
Kawashima, Hiroyuki
Sugaya, Fumiaki
Hashimoto, Masayuki
COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, CICLING 2017, PT II, 2018, 10762 : 180 - 191
[47] SER: Speech Emotion Recognition Application Based on Extreme Learning Machine
Ainurrochman
Febriansyah, Irfanur Ilham
Yuhana, Umi Laili
PROCEEDINGS OF 2021 13TH INTERNATIONAL CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGY AND SYSTEM (ICTS), 2021, : 179 - 183
[48] Speech emotion recognition method in educational scene based on machine learning
Zhang, Yanning
Srivastava, Gautam
EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS, 2022, 9 (05)
[49] Ensemble of Machine Learning and Acoustic Segment Model Techniques for Speech Emotion and Autism Spectrum Disorders Recognition
Lee, Hung-yi
Hu, Ting-yao
Jing, How
Chang, Yun-Fan
Tsao, Yu
Kao, Yu-Cheng
Pao, Tsang-Long
14TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2013), VOLS 1-5, 2013, : 215 - 219
[50] Speech Emotion Recognition using Decomposed Speech via Multi-task Learning
Hsu, Jia-Hao
Wu, Chung-Hsien
Wei, Yu-Hung
INTERSPEECH 2023, 2023, : 4553 - 4557

← 1 2 3 4 5 →