Hybrid LSTM-Transformer Model for Emotion Recognition from Speech Audio Files
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DOI: 10.1109/access.2022.3163856
Abstract: Emotion is a vital component in daily human communication and it helps people understand each other. Emotion recognition plays a crucial role in developing human-computer interaction and computer-based speech emotion recognition. In a nutshell, Speech… read more here.
Keywords: recognition; emotion; lstm transformer; model ... See more keywords
Improving Weather Predictions Accuracy With a Hybrid LSTM-Transformer Model: A Study on Indian Climate
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DOI: 10.1109/access.2025.3614473
Abstract: Weather prediction is a challenging task, particularly in dealing with the diverse geography and weather patterns of various Indian cities throughout the year. This research presents an optimized hybrid model (OHM) that combines long-short-term memory… read more here.
Keywords: various indian; lstm transformer; weather; model ... See more keywords
Transfer learning-driven prediction of oil and gaspipeline corrosion rates in small sample scenarios
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DOI: 10.1371/journal.pone.0333914
Abstract: To ensure the safe operation of oil and gas pipeline systems in complex environments, accurately predicting the corrosion rate of natural gas well pipes is of paramount importance. Given the widespread challenge of pipe corrosion… read more here.
Keywords: transfer learning; small sample; lstm transformer; corrosion ... See more keywords
Comparative Evaluation of Sequential Neural Network (GRU, LSTM, Transformer) Within Siamese Networks for Enhanced Job–Candidate Matching in Applied Recruitment Systems
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DOI: 10.3390/app15115988
Abstract: Job–candidate matching is pivotal in recruitment, yet traditional manual or keyword-based methods can be laborious and prone to missing qualified candidates. In this study, we introduce the first Siamese framework that systematically contrasts GRU, LSTM,… read more here.
Keywords: candidate matching; lstm transformer; transformer; job candidate ... See more keywords