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Institution

University of Avignon

EducationAvignon, Provence-Alpes-Côte-d'Azur, France
About: University of Avignon is a education organization based out in Avignon, Provence-Alpes-Côte-d'Azur, France. It is known for research contribution in the topics: Population & Speaker recognition. The organization has 1526 authors who have published 3766 publications receiving 88928 citations.


Papers
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Journal ArticleDOI
TL;DR: This review presents a complete picture of current knowledge on application of ultrasound in food technology including processing, preservation and extraction and provides the necessary theoretical background and some details about ultrasound the technology, the technique, and safety precautions.

1,963 citations

Journal ArticleDOI
TL;DR: This review presents a complete picture of current knowledge on ultrasound-assisted extraction in food ingredients and products, nutraceutics, cosmetic, pharmaceutical and bioenergy applications, and applications from laboratory to industry, security, and environmental impacts.

1,657 citations

Journal ArticleDOI
TL;DR: The six principles of green-extraction are introduced, describing a multifaceted strategy to apply this concept at research and industrial level, and offer an updated glimpse of the huge technological effort that is being made and the diverse applications that are being developed.
Abstract: The design of green and sustainable extraction methods of natural products is currently a hot research topic in the multidisciplinary area of applied chemistry, biology and technology. Herein we aimed to introduce the six principles of green-extraction, describing a multifaceted strategy to apply this concept at research and industrial level. The mainstay of this working protocol are new and innovative technologies, process intensification, agro-solvents and energy saving. The concept, principles and examples of green extraction here discussed, offer an updated glimpse of the huge technological effort that is being made and the diverse applications that are being developed.

1,145 citations

Journal ArticleDOI
TL;DR: An introduction proposes a modular scheme of the training and test phases of a speaker verification system, and the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed.
Abstract: This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture modeling, which is the speaker modeling technique used in most systems, is then explained. A few speaker modeling alternatives, namely, neural networks and support vector machines, are mentioned. Normalization of scores is then explained, as this is a very important step to deal with real-world data. The evaluation of a speaker verification system is then detailed, and the detection error trade-off (DET) curve is explained. Several extensions of speaker verification are then enumerated, including speaker tracking and segmentation by speakers. Then, some applications of speaker verification are proposed, including on-site applications, remote applications, applications relative to structuring audio information, and games. Issues concerning the forensic area are then recalled, as we believe it is very important to inform people about the actual performance and limitations of speaker verification systems. This paper concludes by giving a few research trends in speaker verification for the next couple of years.

874 citations

Journal ArticleDOI
TL;DR: An analysis of speaker diarization performance as reported through the NIST Rich Transcription evaluations on meeting data and identify important areas for future research are presented.
Abstract: Speaker diarization is the task of determining “who spoke when?” in an audio or video recording that contains an unknown amount of speech and also an unknown number of speakers. Initially, it was proposed as a research topic related to automatic speech recognition, where speaker diarization serves as an upstream processing step. Over recent years, however, speaker diarization has become an important key technology for many tasks, such as navigation, retrieval, or higher level inference on audio data. Accordingly, many important improvements in accuracy and robustness have been reported in journals and conferences in the area. The application domains, from broadcast news, to lectures and meetings, vary greatly and pose different problems, such as having access to multiple microphones and multimodal information or overlapping speech. The most recent review of existing technology dates back to 2006 and focuses on the broadcast news domain. In this paper, we review the current state-of-the-art, focusing on research developed since 2006 that relates predominantly to speaker diarization for conference meetings. Finally, we present an analysis of speaker diarization performance as reported through the NIST Rich Transcription evaluations on meeting data and identify important areas for future research.

706 citations


Authors

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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202268
2021226
2020242
2019239
2018234