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Urszula Libal and Pawel Biernacki
An automatic honey bee classification system based on audio signals for tracking the frequency of workers and drones entering and leaving a hive.
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Uma Rajasekaran, Mohanaprasad Kothandaraman and Chang Hong Pua
Significant water loss caused by pipeline leaks emphasizes the importance of effective pipeline leak detection and localization techniques to minimize water wastage. All of the state-of-the-art approaches use deep learning (DL) for leak detection and cro...
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Sai Bharadwaj Appakaya, Ruchira Pratihar and Ravi Sankar
Parkinson?s disease (PD) classification through speech has been an advancing field of research because of its ease of acquisition and processing. The minimal infrastructure requirements of the system have also made it suitable for telemonitoring applicat...
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Matthieu Saumard
Speech Emotions Recognition (SER) has gained significant attention in the fields of human?computer interaction and speech processing. In this article, we present a novel approach to improve SER performance by interpreting the Mel Frequency Cepstral Coeff...
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Tareq Khan
Gun violence and mass shootings kill and injure people, create psychological trauma, damage properties, and cause economic loss. The loss from gun violence can be reduced if we can detect the gunshot early and notify the police as soon as possible. In th...
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Wondimu Lambamo, Ramasamy Srinivasagan and Worku Jifara
The performance of speaker recognition systems is very well on the datasets without noise and mismatch. However, the performance gets degraded with the environmental noises, channel variation, physical and behavioral changes in speaker. The types of Spea...
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Shuang Yang, Lingzhi Xue, Xi Hong and Xiangyang Zeng
Recently, deep learning has been widely used in ship-radiated noise classification. To improve classification efficiency, avoiding high computational costs is an important research direction in ship-radiated noise classification. We propose a lightweight...
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Qiang Zhu, Zhong Wang, Yunfeng Dou and Jian Zhou
A conversion method based on the inversion of Mel frequency cepstral coefficient (MFCC) features was proposed to convert whispered speech into normal speech. First, the MFCC features of whispered speech and normal speech were extracted and a matching rel...
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Amira Dhouib, Achraf Othman, Oussama El Ghoul, Mohamed Koutheair Khribi and Aisha Al Sinani
Automatic Speech Recognition (ASR), also known as Speech-To-Text (STT) or computer speech recognition, has been an active field of research recently. This study aims to chart this field by performing a Systematic Literature Review (SLR) to give insight i...
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Sakshi Dua, Sethuraman Sambath Kumar, Yasser Albagory, Rajakumar Ramalingam, Ankur Dumka, Rajesh Singh, Mamoon Rashid, Anita Gehlot, Sultan S. Alshamrani and Ahmed Saeed AlGhamdi
Deep learning-based machine learning models have shown significant results in speech recognition and numerous vision-related tasks. The performance of the present speech-to-text model relies upon the hyperparameters used in this research work. In this re...
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