Visual object tracking has significantly promoted autonomous applications for unmanned aerial vehicles (UAVs). However, learning robust object representations for UAV tracking is especially challenging in complex dyna...
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Introduction: Computing Salient Feature Points (SFP) of 3D models has important application value in the field of computer graphics. In order to extract the SFP more effectively, a novel SFP computing algorithm based ...
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In the process of delivery usually the baby comes out of the vagina but under some circumstances a cesarean section is performed. Caesarean section, on the one hand can have short-term and long-term effects for the mo...
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Travel demand forecasting (TDF) is a crucial task in route planning, navigation, and scheduling. However, developing models for such tasks requires significant amount of order data, which can pose privacy concerns for...
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Existing research on speaker and emotional voice conversion often focuses on separate tasks, neglecting their joint exploration. Furthermore, the limited availability of emotional corpora for target speakers poses a s...
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ISBN:
(数字)9798331522667
ISBN:
(纸本)9798331522674
Existing research on speaker and emotional voice conversion often focuses on separate tasks, neglecting their joint exploration. Furthermore, the limited availability of emotional corpora for target speakers poses a significant challenge for training robustness and generalized models. This paper proposes an improved scheme for speaker-emotion voice conversion with limited target speaker's emotional corpus, integrating a large language model and a pre-trained emotional speech synthesis model. It introduces several enhancements to enhance the quality of converted speech in terms of speaker similarity and emotional expressiveness. First, emotionally tagged text is generated using a large language model and emotional speech is synthesized from this text using a fine-tuned pre-trained emotional speech synthesis model. Then, a speaker-emotion voice conversion model is co-trained with both synthesized and real target emotional speech. Finally, the model is fine-tuned with the real target emotional speech to further boost the speaker and emotional similarity.
As an emerging technology that has already impacted various sectors including finance, energy, education, and more, blockchain provides a decentralized ledger system that ensures the integrity of the recorded transact...
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The availability of important characteristics such as decentralization, permanence, anonymity, and audacity has driven interest in blockchain technology more recently than ever before. This technology has been employe...
The availability of important characteristics such as decentralization, permanence, anonymity, and audacity has driven interest in blockchain technology more recently than ever before. This technology has been employed in a variety of applications, including education. Therefore, this research is a systematic review of research that investigates the applications of blockchain technology in higher education institutions in addition to those that present the role of this technology in combating the Corona pandemic, as it focuses on the following main topics: (1) blockchain-based applications and systems that can be used in higher education institutions; and (2) the current state of blockchain challenges in this area that need to be addressed in the future. A detailed analysis of the results of each topic as well as an extensive discussion were conducted based on the results. This review also provides insight into other areas that could benefit from blockchain technology during and after the pandemic.
Voice recognition systems are crucial because they allow seamless human-computer interaction and improve accessibility for users of all abilities. The use of these technologies in hands-free control, language translat...
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ISBN:
(数字)9798331504465
ISBN:
(纸本)9798331504472
Voice recognition systems are crucial because they allow seamless human-computer interaction and improve accessibility for users of all abilities. The use of these technologies in hands-free control, language translation, virtual assistants, transcription services, and hands-free control is revolutionising how we engage with technology and enhancing convenience and productivity in general. Several attendance systems based on voice recognition exist, but we wanted to deploy an attendance system with a good graphical user interface specifically for students of GIK Institute. For this purpose, we wanted to make a user-friendly and accurate voice recognition system based and trained on self-provided data of ten students. This study introduces an AI-driven attendance system, which demonstrates high efficiency and accuracy in identifying students’ daily class attendance. To achieve this, the Gaussian Mixture Model approach was employed. The paper also delves into the utilization of libraries and methods, encompassing the training and validation of well-known machine learning models. Additionally, the system’s performance, its strengths, weaknesses and potential areas for improvement are also discussed in the study.
The electrically evoked compound action potential (ECAP) has been used in various clinical studies and has become a key physiological signal for cochlear implants (CI). This study used four sensing electrodes to recor...
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ISBN:
(数字)9798350348958
ISBN:
(纸本)9798350348965
The electrically evoked compound action potential (ECAP) has been used in various clinical studies and has become a key physiological signal for cochlear implants (CI). This study used four sensing electrodes to record ECAP signals based on the alternating polarity approach. An electrical field imaging (EFI) result based on the finite element method was used to obtain the interface impedance, then ECAP simulation results were computed and compared with a patient's clinical ECAP measurements. Preliminary modeling results show that the interface impedance obtained by this EFI-based technique can improve the simulation accuracy of the ECAP model. The ECAP modeling result will be compared with clinical ECAP measurements to validate the model in the full paper.
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