Deep learning techniques for speech emotion recognition: A review by Silviana Widya Lestari, Saliyah Kahar, Trismayanti Dwi

“…Speech emotion recognition is gaining significant importance in the domains of pattern recognition and natural language processing. In recent years, there has been notable progress in voice emotion detection within this field, primarily attributed to the successful application of deep learning techniques. …”
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Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…Rapid advancements in natural language processing models have led to the generation of text closely resembling human language, making it increasingly difficult to differentiate between human and AI-generated content. …”
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Recognition model for major depressive disorder in Arabic user-generated content by Esraa M. Rabie, Atef F. Hashem, Fahad Kamal Alsheref

“…This research offers a novel framework for depression detection from Arabic textual data utilizing deep learning (DL), natural language processing (NLP), machine learning (ML), and BERT transformers techniques in light of the disease’s high prevalence. …”
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Enhanced Hybrid Deep Learning Model With Improved Self-Attention Mechanism for Legal Judgment Prediction by G. Sukanya, J. Priyadarshini

“…The dawn of Natural Language Processing in the legal research field has achieved great heights. …”
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LSV-MAE: A Masked-Autoencoder Pre-Training Approach for Large-Scale 3D Point Cloud Data by Nuo Cheng, Chuanyu Luo, Han Li, Sikun Ma, Shengguang Lei, Pu Li

“…Masked language modeling (MLM) and masked image modeling (MIM) pretraining paradigms have achieved remarkable success in both natural language processing (NLP) and computer vision (CV). However, extending MIM to large-scale outdoor point cloud data presents significant challenges due to the inherent sparsity and wide spatial coverage of such data. …”
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Building Safer Social Spaces: Addressing Body Shaming with LLMs and Explainable AI by Sajedeh Talebi, Neda Abdolvand

“…These findings advance Natural Language Processing (NLP) for cyberbullying detection, promoting safer social media environments.…”
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Genie: Enhancing information management in the restaurant industry through AI-powered chatbot by Megha Gupta, Venkatasai Dheekonda, Mohammad Masum

“…Designed to enhance restaurant operations including order processing, reservations, and FAQs management, Genie leverages advanced Natural Language Processing (NLP) techniques. By converting input queries into word embeddings and applying a sophisticated tag classification system, Genie precisely interprets customer intents and generates accurate responses, thereby markedly improving the dining experience. …”
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An explainable RoBERTa approach to analyzing panic and anxiety sentiment in oral health education YouTube comments by Pradeep Kumar Yadalam, Mohamed Thaha, Prabhu Manickam Natarajan, Carlos M. Ardila

“…This study uses RoBERTa, a state-of-the-art language model, to advance Natural Language Processing (NLP) research and enable real-time feedback in social media environments. …”
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Packaging Design Image Segmentation Based on Improved Full Convolutional Networks by Chunxiao Zhang, Mengmeng Han, Jingjing Jia, Chulsoo Kim

“…In recent years, advancements in machine learning, particularly in the field of natural language processing (NLP), have paved the way for novel methods in other areas, such as image processing and packaging design. …”
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Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients. by Maria Mahbub, Sudarshan Srinivasan, Ioana Danciu, Alina Peluso, Edmon Begoli, Suzanne Tamang, Gregory D Peterson

“…In this work, we propose a framework to predict short, mid, and long-term mortality in adult ICU patients using unstructured clinical notes from the MIMIC III database, natural language processing (NLP), and machine learning (ML) models. …”
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Quantized convolutional neural networks: a hardware perspective by Li Zhang, Olga Krestinskaya, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama

“…With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with classic machine learning techniques. …”
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A hybrid approach for pattern recognition and interpretation in age-related false memory by Noorbakhsh Amiri Golilarz, Elias Hossain, Shahram Rahimi, Hossein Karimi

“…IntroductionAging is associated with a decline in essential cognitive functions such as language processing, memory, and attention, which significantly impacts the quality of life in later years. …”
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Next-Value Prediction of Beam Waists From Mixed Pitch Grating Using Simplified Transformer Model by Yu Dian Lim, Peng Zhao, Luca Guidoni, Jean-Pierre Likforman, Chuan Seng Tan

“…This study provides a pioneering approach to using natural language processing model to perform predictive modelling on photonics data, and possible extrapolation of photonics data using transformer model.…”
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Skills Prediction for the South African Food and Beverages Manufacturing Sector by Megashnee Munsamy, Arnesh Telukdarie

“…The source of big data is skills-related publications from the Elsevier Scopus database, for the period 1999 to 2020. Natural language processing, and word representation technique was applied to quantify and analyse year-on-year change of author and index keywords, subject areas and number of publications towards the determination of the future skills requirement. …”
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Sentiment works in small-cap stocks: Japanese stock’s sentiment with language models by Masahiro Suzuki, Yasushi Ishikawa, Masayuki Teraguchi, Hiroki Sakaji

“…Language models such as BERT and ChatGPT are advancing the application of natural language processing (NLP) to financial fields. We construct multiple sentiment calculation methods using sentiment dictionaries, models trained on existing sentiment datasets, ChatGPT, and GPT-4. …”
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FPG-AI RNN: A Technology-Agnostic Framework for the Automatic Acceleration of LSTM/GRU-Based Models on FPGAs by Tommaso Pacini, Pietro Nannipieri, Silvia Moranti, Luca Fanucci

“…Recurrent Neural Networks (RNNs) are pivotal in artificial intelligence, excelling in tasks involving sequential data across fields such as natural language processing and time-series forecasting. FPGAs have emerged as an efficient technology for accelerating these algorithms, especially in resource- and power-constrained platforms such as edge devices. …”
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Development of an artificial intelligence-enhanced warfarin interaction checker platform. by Monther Abdolmohsin Alsultan, Mohammed Alabdulmuhsin, Deema AlBunyan

“…Warfa-Check, developed with Python and Flask as well as OpenAI's GPT-4 API with natural language processing tools trained to correctly interpret outbound warfarin interactions. …”
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Information Retrieval Based on Brazilian Portuguese Texts by Victor Hayashi, Mateus Carvalho, João Carlos Néto, Felipe Pinna, Rosangela Marquesone, Wilson Ruggiero, Maisa Duarte

“…By combining Natural Language Processing techniques (e.g., syntactic analysis to obtain the logical meaning of sentences based on rules and its structure) and an ontology constructor library, it was possible to build a tool that receives texts from the banking domain and constructs an ontology that knowledge-based intelligent systems can use. …”
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MindLift: AI-powered mental health assessment for students by Shanky Goyal, RishiRaj Dutta, Saurabh Dev, Kola Narasimha Raju, Mohammed Wasim Bhatt

“…By integrating convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer-based natural language processing (NLP) models, MindLift provides a comprehensive emotional analysis. …”
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A benchmark for evaluating crisis information generation capabilities in LLMs by Ruilian Han, Lu An, Wei Zhou, Gang Li

“…Large language models (LLMs) have become increasingly significant in crisis information management due to their advanced natural language processing capabilities. This study aims to develop a comprehensive evaluation benchmark to assess the effectiveness of LLMs in generating crisis information. …”
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