Proceedings of the 23th International Workshop on Software and Compilers for Embedded Systems 2020
DOI: 10.1145/3378678.3397528
|View full text |Cite
|
Sign up to set email alerts
|

Real-time audio processing for hearing aids using a model-based bayesian inference framework

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 10 publications
0
1
0
Order By: Relevance
“…It features adaptive differential microphones [ 35 ] and provides hearing loss compensation based on the Camfit compressive gain prescription rule [ 36 ]. openMHA was integrated with the Julia programming language [ 22 ] to implement Bayesian machine learning techniques for real-time hearing aid processing. The real-time capabilities of openMHA were also used in an computer vision application for real-time feature extraction and classification of posture and gesture [ 23 ].…”
Section: Motivation and Significancementioning
confidence: 99%
“…It features adaptive differential microphones [ 35 ] and provides hearing loss compensation based on the Camfit compressive gain prescription rule [ 36 ]. openMHA was integrated with the Julia programming language [ 22 ] to implement Bayesian machine learning techniques for real-time hearing aid processing. The real-time capabilities of openMHA were also used in an computer vision application for real-time feature extraction and classification of posture and gesture [ 23 ].…”
Section: Motivation and Significancementioning
confidence: 99%