Abstract
Audio signal modeling and simulation is important in several coding, noise removal, and recognition applications. This paper focuses on implementing models for loudness estimation and their use in estimating parameters on iOS mobile devices (iPhones and iPads). We briefly address estimating excitation patterns and loudness through auditory models. These loudness estimation and other algorithms were implemented in the award winning educational iOS app iJDSP for performing DSP simulations on mobile devices. The modules were introduced to graduate students in the general signal processing area, to evaluate their effectiveness as teaching tools. The evaluation process involved giving the students a pre-quiz, guiding them through hands-on activities on the iOS app, and finally, a post-quiz. Assessments results were positive with noticeable improvement of student understanding of topics such as spectrograms and linear predictive coding.
| Original language | English (US) |
|---|---|
| Title of host publication | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 5550-5554 |
| Number of pages | 5 |
| Volume | 2015-August |
| ISBN (Print) | 9781467369978 |
| DOIs | |
| State | Published - Aug 4 2015 |
| Event | 40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia Duration: Apr 19 2014 → Apr 24 2014 |
Other
| Other | 40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 |
|---|---|
| Country | Australia |
| City | Brisbane |
| Period | 4/19/14 → 4/24/14 |
Fingerprint
Keywords
- auditory pattern
- iJDSP
- iOS
- Loudness estimation
- mobile education
ASJC Scopus subject areas
- Signal Processing
- Software
- Electrical and Electronic Engineering
Cite this
Audio modeling and loudness estimation with IJDSP mobile simulations. / Kalyanasundaram, Girish; Banavar, Mahesh; Spanias, Andreas.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Vol. 2015-August Institute of Electrical and Electronics Engineers Inc., 2015. p. 5550-5554 7179033.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Audio modeling and loudness estimation with IJDSP mobile simulations
AU - Kalyanasundaram, Girish
AU - Banavar, Mahesh
AU - Spanias, Andreas
PY - 2015/8/4
Y1 - 2015/8/4
N2 - Audio signal modeling and simulation is important in several coding, noise removal, and recognition applications. This paper focuses on implementing models for loudness estimation and their use in estimating parameters on iOS mobile devices (iPhones and iPads). We briefly address estimating excitation patterns and loudness through auditory models. These loudness estimation and other algorithms were implemented in the award winning educational iOS app iJDSP for performing DSP simulations on mobile devices. The modules were introduced to graduate students in the general signal processing area, to evaluate their effectiveness as teaching tools. The evaluation process involved giving the students a pre-quiz, guiding them through hands-on activities on the iOS app, and finally, a post-quiz. Assessments results were positive with noticeable improvement of student understanding of topics such as spectrograms and linear predictive coding.
AB - Audio signal modeling and simulation is important in several coding, noise removal, and recognition applications. This paper focuses on implementing models for loudness estimation and their use in estimating parameters on iOS mobile devices (iPhones and iPads). We briefly address estimating excitation patterns and loudness through auditory models. These loudness estimation and other algorithms were implemented in the award winning educational iOS app iJDSP for performing DSP simulations on mobile devices. The modules were introduced to graduate students in the general signal processing area, to evaluate their effectiveness as teaching tools. The evaluation process involved giving the students a pre-quiz, guiding them through hands-on activities on the iOS app, and finally, a post-quiz. Assessments results were positive with noticeable improvement of student understanding of topics such as spectrograms and linear predictive coding.
KW - auditory pattern
KW - iJDSP
KW - iOS
KW - Loudness estimation
KW - mobile education
UR - http://www.scopus.com/inward/record.url?scp=84946062896&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946062896&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2015.7179033
DO - 10.1109/ICASSP.2015.7179033
M3 - Conference contribution
AN - SCOPUS:84946062896
SN - 9781467369978
VL - 2015-August
SP - 5550
EP - 5554
BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -