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Proceedings ArticleDOI

Recognition of blowing sound types for real-time implementation in mobile devices

TLDR
A system to recognize and classify sounds produced by human subjects blowing air by the mouth using low-complexity algorithms in a low-budget processor and a naive Bayes classifier is presented.
Abstract
This paper presents a system to recognize and classify sounds produced by human subjects blowing air by the mouth. The objective is to implement the system for fast recognition using low-complexity algorithms in a low-budget processor. Recognition is achieved using tailored band energy ratios, modified frequency centroid and a periodicity test based on spectrum autocorrelation. These lightweight feature extraction techniques are adapted to the particular task of recognition of blowing sound types. The classification is achieved by a naive Bayes classifier. The algorithm can be implemented in real-time (latency ≤ 100 ms) and experimental test results show average recognition rates over 94 %.

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Citations
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Proceedings ArticleDOI

Recasting the data sublime in media architecture

TL;DR: This essay speculates on some of the relationships that might exist between data sublimity and placemaking in design research and contributes to the literature by engaging in a reflection on how the data sublime could be recast and applied to media architecture.
Journal ArticleDOI

A Computer Mouse Using Blowing Sensors Intended for People with Disabilities.

TL;DR: An innovative blowing-controlled mouse assistive tool that uses microphones to induce small signals through the principle of airflow vibration, and it then converts the received signal into the corresponding pulse width and has the benefits of low cost and humanized operation.
Journal ArticleDOI

A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations

TL;DR: The main objective is to obtain a person’s lung age by analyzing the properties of their exhalation by means of a machine-learning method and it is found that the best classification algorithm was the Quadratic Linear Discriminant algorithm when no distinction was made between gender.
Book ChapterDOI

Automatic Quality Assessment of a Forced Expiratory Manoeuvre Acquired with the Tablet Microphone

TL;DR: This method provides immediate feedback to the user, by grading the manoeuvre in a visual scale, promoting the repetition of the FEM when needed, and using 498 FEM recordings, both specificity and sensitivity attained were above 90%.
References
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Journal ArticleDOI

On the Optimality of the Simple Bayesian Classifier under Zero-One Loss

TL;DR: The Bayesian classifier is shown to be optimal for learning conjunctions and disjunctions, even though they violate the independence assumption, and will often outperform more powerful classifiers for common training set sizes and numbers of attributes, even if its bias is a priori much less appropriate to the domain.
Book

Clinical measurement of speech and voice

TL;DR: Analog Electronics.
Journal ArticleDOI

Idiot's Bayes—Not So Stupid After All?

TL;DR: In this article, the authors examine the evidence for this, both empirical, as observed in real data applications, and theoretical, summarising explanations for why this simple rule might be effective.
Journal ArticleDOI

Environmental Sound Recognition With Time–Frequency Audio Features

TL;DR: An empirical feature analysis for audio environment characterization is performed and a matching pursuit algorithm is proposed to use to obtain effective time-frequency features to yield higher recognition accuracy for environmental sounds.
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