(Subscribe to this discussion)

Modern feature-based methodologies in semantic audio applications attempt to capture the temporal dependency of successive feature observations, which form the so-called texture windows. This paper proposes an enhancement of this type of processing, known as temporal feature integration, by employing and testing alternative deployable strategies. Specifically, data are fitted through commonly used statistical principles, estimating the parameters of a given probability density function that maximize the log-likelihood of the samples inside each texture window. The main statistical model that is set under investigation is the alpha-stable distribution because it can successfully represent signals, which the commonly used Gaussian curves fail to capture. Within this framework, the enhanced feature integration method is also elaborated, introducing new measures for feature modeling. The main objective of this work is to introduce an efficient feature engineering protocol for temporal integration, specifying a compact and robust set of aggregated audio parameters that can address the needs of many audio information retrieval systems.

Authors: Vrysis, Lazaros; Hadjileontiadis, Leontios; Thoidis, Iordanis; Dimoulas, Charalampos; Papanikolaou, George
Affiliations: Aristotle University of Thessaloniki, Thessaloniki, Greece; Khalifa University of Science and Technology, Abu Dhabi, UAE; Aristotle University of Thessaloniki, Thessaloniki, Greece; Aristotle University of Thessaloniki, Thessaloniki, Greece; Aristotle University of Thessaloniki, Thessaloniki, Greece(See document for exact affiliation information.)
JAES Volume 69 Issue 4 pp. 227-237; April 2021
Publication Date: April 8, 2021

Click to purchase paper as a non-member or you can login as an AES member to see more options.

(Comment on this paper)

Comments on this paper

Francesco Balena

Comment posted April 29, 2021 @ 15:53:54 UTC (Comment permalink) I had completely misunderstood the content of thie article. I was thinking about the MOSFET thresholds....It is welcome to address the problem of gender equality also in audio. But as with gender disparities in other fields, what matters is competence. The male-dominated obstacles to female competence must be severely fought. After that it is only a cultural question in female's choices. Francesco Balena (Respond to this comment)

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Join this discussion!

If you would like to contribute to the discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.