Results 41 to 50 of about 3,813 (182)
Utilizing MFCCs and TEO-MFCCs to Classify Stress in Females Using SSNNA
All individuals are susceptible to experiencing stress in their everyday lives. Nevertheless, stress has a greater influence on females due to both biological and environmental factors. This study utilized female speeches to detect and classify stress and no stress in women.
Nur Aishah Zainal +5 more
openaire +2 more sources
Passive Acoustic Identification of Social Groups in the Hainan Gibbon
Passive acoustic monitoring offers a non‐invasive means of assessing visually hard‐to‐survey wildlife species with distinctive vocalizations. We evaluated whether deep learning can identify Hainan gibbon (Nomascus hainanus) social groups from their calls.
Emmanuel Kabuga +14 more
wiley +1 more source
The paper proposes a framework to record meeting to avoid hassle of writing points of meeting. Key components of framework are “Model Trainer” and “Meeting Recorder”.
Khan Isra +3 more
doaj +1 more source
AI‐accelerated passive acoustic monitoring reveals extensive bomb fishing within the Spermonde Archipelago, with annual incidents numbering in the thousands. ABSTRACT Bomb fishing is recognised as the most destructive fishing practice that can be performed in our oceans.
Ben Williams +9 more
wiley +1 more source
Comparison of VTOL UAV Battery Level for Propeller Faulty Classification Model
The degradation of batteries in UAVs may result in various problems, such as connectivity troubles, flight delays, and unexpected accidents. Flight safety and reliability are affected by propeller efficiency and performance.
Fareisya Zulaikha Mohd Sani +4 more
doaj +1 more source
Multi-Accent Speaker Detection Using Normalize Feature MFCC Neural Network Method
Speaker recognition is a field of research that continues to this day. Various methods have been developed to detect the human voice with greater precision and accuracy. Research on human speech recognition that is quite challenging is accent recognition.
Kristiawan Nugroho +3 more
doaj +1 more source
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley +1 more source
Pistachio Classification Based on Acoustic Systems and Machine Learning
An acoustic emission and machine learning based pistachio classification system has been developed. This system performs feature extraction using Mel frequency cepstral coefficients (MFCC) and classification using support vector machine (SVM). This study
Yavuz Türkay, Zekiye Seyma Tamay
doaj +1 more source
Bidirectional deep architecture for Arabic speech recognition
Nowadays, the real life constraints necessitates controlling modern machines using human intervention by means of sensorial organs. The voice is one of the human senses that can control/monitor modern interfaces.
Zerari Naima +3 more
doaj +1 more source
CNN AND LSTM FOR THE CLASSIFICATION OF PARKINSON'S DISEASE BASED ON THE GTCC AND MFCC
Parkinson's disease is a recognizable clinical syndrome with a variety of causes and clinical presentations; it represents a rapidly growing neurodegenerative disorder.
Nouhaila BOUALOULOU +2 more
doaj +1 more source

