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Sound

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High-Level CNN and Machine Learning Methods for Speaker Recognition.

Sensors (Basel, Switzerland)
Speaker Recognition (SR) is a common task in AI-based sound analysis, involving structurally different methodologies such as Deep Learning or "traditional" Machine Learning (ML). In this paper, we compared and explored the two methodologies on the DE...

A Multimodal Dataset for Automatic Edge-AI Cough Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. Automatic cough counting tools must provide accurate information, while ...

Evaluating the Performance of Pre-Trained Convolutional Neural Network for Audio Classification on Embedded Systems for Anomaly Detection in Smart Cities.

Sensors (Basel, Switzerland)
Environmental Sound Recognition (ESR) plays a crucial role in smart cities by accurately categorizing audio using well-trained Machine Learning (ML) classifiers. This application is particularly valuable for cities that analyzed environmental sounds ...

ORCA-SPY enables killer whale sound source simulation, detection, classification and localization using an integrated deep learning-based segmentation.

Scientific reports
Acoustic identification of vocalizing individuals opens up new and deeper insights into animal communications, such as individual-/group-specific dialects, turn-taking events, and dialogs. However, establishing an association between an individual an...

Classification of crispness of food materials by deep neural networks.

Journal of texture studies
Crispness is a textural characteristic that influences consumer choices, requiring a comprehensive understanding for product customization. Previous studies employing neural networks focused on acquiring audio through mechanical crushing of crispy sa...

Decision Tree Versus Linear Support Vector Machine Classifier in the Screening of Medial Speech Sounds: A Quest for a Sound Rationale.

Studies in health technology and informatics
This paper describes the latest development in the classification stage of our Speech Sound Disorder (SSD) Screening algorithm and presents the results achieved by using two classifier models: the Classification and Regression Tree (CART)-based model...

Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning.

Ultrasonics
Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast t...

Heterogeneous fusion of biometric and deep physiological features for accurate porcine cough recognition.

PloS one
Accurate identification of porcine cough plays a vital role in comprehensive respiratory health monitoring and diagnosis of pigs. It serves as a fundamental prerequisite for stress-free animal health management, reducing pig mortality rates, and impr...

Passive exposure to task-relevant stimuli enhances categorization learning.

eLife
Learning to perform a perceptual decision task is generally achieved through sessions of effortful practice with feedback. Here, we investigated how passive exposure to task-relevant stimuli, which is relatively effortless and does not require feedba...

Research on Pig Sound Recognition Based on Deep Neural Network and Hidden Markov Models.

Sensors (Basel, Switzerland)
In order to solve the problem of low recognition accuracy of traditional pig sound recognition methods, deep neural network (DNN) and Hidden Markov Model (HMM) theory were used as the basis of pig sound signal recognition in this study. In this study...