ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH
An on-line unsupervised algorithm for estimating the hidden Markov models (HMM) parame-ters is presented. The problem of hidden Markov models adaptation to emotional speech is solved. To increase the reliability of estimated HMM parameters, a mechanism of forgetting and updating is proposed. A funct...
Saved in:
Main Author: | A. V. Tkachenia |
---|---|
Format: | Article |
Language: | Russian |
Published: |
National Academy of Sciences of Belarus, the United Institute of Informatics Problems
2016-10-01
|
Series: | Informatika |
Online Access: | https://inf.grid.by/jour/article/view/152 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hidden Markov Model-Based Video Recognition for Sports
by: Zhiyuan Wang, et al.
Published: (2021-01-01) -
Learning Evolutionary Stages with Hidden Semi-Markov Model for Predicting Social Unrest Events
by: Fengcai Qiao, et al.
Published: (2020-01-01) -
Visual tracking using interactive factorial hidden Markov models
by: Jin Wook Paeng, et al.
Published: (2021-08-01) -
Retracted: Multimedia Recognition of Piano Music Based on the Hidden Markov Model
by: Advances in Multimedia
Published: (2023-01-01) -
An Online Map Matching Algorithm Based on Second-Order Hidden Markov Model
by: Xiao Fu, et al.
Published: (2021-01-01)