Understanding the Use of Acoustic Measurement and Mel Frequency Cepstral Coefficient (MFCC) Features for the Classification of Depression Speech
Depression has been affecting people all around the world, including Malaysians. Early detection mechanisms are vital for assisting clinical professionals in identifying depressed patients at an early stage. Although this can be accomplished through interviews and questionnaires, the time-consuming...
Saved in:
Main Authors: | Shanmugam M., Ismail N.N.N., Magalingam P., Hashim N.N.W.N., Singh D. |
---|---|
Other Authors: | 36195134500 |
Format: | Book chapter |
Published: |
Springer Science and Business Media Deutschland GmbH
2024
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Simulink model of Mel Frequency Cepstral Coefficient analysis for extracting asphyxiated infant cry features
by: Mohebbi Zulfikar, Mohd Ali, et al.
Published: (2012) -
Speech recognition using MFCC and DTW classifier
by: Mukrimah, Nawir
Published: (2016) -
Classification of speech dysfluencies with MFCC and LPCC features
by: Ooi, Chia Ai, et al.
Published: (2011) -
Infant cry recognition system: A comparison of system performance based on Mel frequency and linear prediction cepstral coefficients
by: Abdulaziz Y., et al.
Published: (2023) -
MFCC based recognition of repetitions and prolongations in stuttered speech using k-NN and LDA
by: Lim, Sin Chee, et al.
Published: (2010)