Multi-cloud environments offer benefits like vendor diversification and resilience but pose challenges such as increased management complexity, lack of cost transparency, and compliance. This concept paper introduces ...
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Approximate computing is a promising paradigm for improving the performance parameters of electronic systems at the expense of accuracy in error-resilient tasks such as multimedia processing, image multiplication, and...
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This study aims to identify factors that influence the adoption of artificial intelligence (AI) technology, specifically the ChatGPT chatbot, in the context of higher education in Indonesia. Using an extended Innovati...
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In current meta of Artificial Intelligence and Machine Learning, Self-Driving has gained a lot of popularity. Due to one-on-many usages of the technology, it becomes a massive challenge to deliver edge-driven technolo...
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Real-world multivariate time series unsupervised anomaly detection is a challenging problem due to intricate temporal correlations. Recently, impressive progress have been made in tackling this issue through the desig...
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Nowadays, when biometric identification is widely used, privacy protection in identification has become a very important issue. In recent years, many scholars have contributed to the biometric authentication with cryp...
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Currently, most research methods for spoken off-topic detection are based on the results of upstream speech recognition tasks. However, upstream speech recognition tasks may introduce issues such as homophones, text r...
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ISBN:
(纸本)9789819794300;9789819794317
Currently, most research methods for spoken off-topic detection are based on the results of upstream speech recognition tasks. However, upstream speech recognition tasks may introduce issues such as homophones, text recognition errors, and semantic confusion. Therefore, this study aims to explore the impact of integrating audio features into text information on off-topic degree assessment. To achieve this goal, we collected a dataset consisting of 2652 responses in question-answering scenarios from public competitions. The data was annotated according to the evaluation guidelines for farmers and herdsmen, creating a dataset named ASAG-TD for assessing off-topic degree in question-answering scenarios. In addition, we conducted research using the pre-trained language model RoBERTa, combined with commonly used neural network models, exploring two aspects: audio features and self-supervised pre-trained acoustic model. Experimental results demonstrate the effectiveness of our method, with the mean absolute error (MAE) of off-topic degree in spoken responses reduced to 0.414 and a Pearson correlation coefficient of 0.95.
In Security stands as a cornerstone in the realm of computing and networking technology. At the heart of every endeavor in network design, planning, construction, and operation lies the pivotal necessity of a robust s...
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Students often struggle with basic programming tasks after their first programming course. Adaptive tutoring systems can support students’ practice by generating tasks, providing feedback, and evaluating students’ p...
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Water Quality Sensors (WQSs) are becoming a promised tool in water quality data assessment and scientific value of aquatic structure. Such sensors are broadly used to produce live results by evaluating major water qua...
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