AI Sound Recognition on Asthma Medication Adherence: Evaluation With the RDA Benchmark Suite

Author:

Nikos Fakotakis Dimitris1ORCID,Nousias Stavros1ORCID,Arvanitis Gerasimos1ORCID,Zacharaki Evangelia I.1ORCID,Moustakas Konstantinos1

Affiliation:

1. Department of Electrical and Computer Engineering, University of Patras, Patras, Greece

Funder

European Regional Development Fund of the European Union

Greek National Funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference134 articles.

1. On the use of zero-crossing rate for an application of classification of percussive sounds;gouyon;Proc COST G-6 Conf Digit Audio Effects (DAFX),2000

2. Direct access in content-based Audio Information Retrieval: A state of the art and challenges

3. Separation of voiced and unvoiced using zero crossing rate and energy of the speech signal;bachu;Proc Amer Soc Eng Educ (ASEE) Zone Conf,2008

4. Voiced/Unvoiced Decision for Speech Signals Based on Zero-Crossing Rate and Energy

5. Monitoring asthma medication adherence through content based audio classification

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