Time-frequency modeling and classification of pathological voices

被引：0

作者：

Umapathy, K ^{[1
]}

Krishnan, S ^{[1
]}

Parsa, V ^{[1
]}

Jamieson, D ^{[1
]}

机构：

[1] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON, Canada

来源：

SECOND JOINT EMBS-BMES CONFERENCE 2002, VOLS 1-3, CONFERENCE PROCEEDINGS: BIOENGINEERING - INTEGRATIVE METHODOLOGIES, NEW TECHNOLOGIES | 2002年

关键词：

pathological voices; time-frequency decomposition; octaves; matching pursuit;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Acoustic measures of vocal function are routinely used for the assessment of disordered voices, and for monitoring patients' progress over the course of therapy. In this paper, speech signals were decomposed using an adaptive time-frequency transform algorithm, and the signal decomposition parameters such as the octave (scale) maximum, octave mean, and frequency ratio were analyzed using statistical pattern analysis method. A classification accuracy of 93.4% was obtained with a database of 212 speech signals (51 normal and 161 pathological cases).

引用

页码：116 / 117

页数：2

共 50 条

[41] Local discriminant time-frequency atoms for signal classification
Jiang, QT
Goh, SS
Lin, ZP
SIGNAL PROCESSING, 1999, 72 (01) : 47 - 52
[42] Time-Frequency Representations for EEG Artifact Classification with CNNs
Tiwary, Hrishikesh
Bhavsar, Arnav
2021 IEEE APPLIED IMAGERY PATTERN RECOGNITION WORKSHOP (AIPR), 2021,
[43] Time-frequency analysis of EEG for improved classification of emotion
Vanitha V.
Krishnan P.
Vanitha, V. (vanikkdi@gmail.com), 2017, Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (23) : 191 - 212
[44] Classification of voltage dips based on time-frequency parameters
Subhani, S.
Weldemariam, L. E.
Cuk, V.
Cobben, J. F. G.
2016 IEEE INTERNATIONAL ENERGY CONFERENCE (ENERGYCON), 2016,
[45] Time-Frequency and Phase Derived Features for Emotion Classification
Lalitha, S.
Chaitanya, K. K.
Teja, G. V. N.
Varma, K. Vijith
Tripathi, Shikha
2015 ANNUAL IEEE INDIA CONFERENCE (INDICON), 2015,
[46] Nonstationary signal classification using time-frequency optimization
Breakenridge, C
ICECS 2003: PROCEEDINGS OF THE 2003 10TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS, VOLS 1-3, 2003, : 132 - 135
[47] Optimized time-frequency distributions for acoustic signal classification
Till, M
Rudolph, S
WAVELET APPLICATIONS VIII, 2001, 4391 : 81 - 91
[48] Environmental Sound Classification based on Time-frequency Representation
Thwe, Khine Zar
War, Nu
2017 18TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNDP 2017), 2017, : 251 - 255
[49] Time-Frequency Approach to Radar Detection, Imaging, and Classification
Thayaparan, Thayananthan
Stankovic, Ljubisa
Amin, Moeness
Chen, Victor
Cohen, Leon
Boashash, Boualem
IET SIGNAL PROCESSING, 2010, 4 (03) : 197 - 200
[50] Time-frequency approach to ECG classification of myocardial infarction
Kayikcioglu, Ilknur
Akdeniz, Fulya
Kose, Cemal
Kayikcioglu, Temel
COMPUTERS & ELECTRICAL ENGINEERING, 2020, 84

← 1 2 3 4 5 →