main webpage W Topic Anomaly Detection arXiv (Cornell University) Emotion Detection in Speech Using Lightweight and Transformer-Based Models: A Comparative and Ablation Study 2025 Emotion recognition from speech plays a vital role in the development of empathetic human-computer interaction systems. This paper presents a comparative analysis of lightweight transformer-based models, DistilHuBERT and PaSST, by classifying six core emotion… Article Open Anomaly Detection Open Article Page

Anomaly Detection

Approach in data analysis In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection ) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. Such examples may arouse suspicions of being generated by a different mechanism, or appear inconsistent with the remainder of that set of data. Anomaly detection finds application in many domains including cybersecurity, medicine, machine vision, statistics, neuroscience, law enforcement and financial fraud to name only a few. Critical Symbolic Virtual Narrative Open Anomaly Detection Open Article Page

Exploring foci of: arXiv (Cornell University) Emotion Detection in Speech Using Lightweight and Transformer-Based Models: A Comparative and Ablation Study 2025 Emotion recognition from speech plays a vital role in the development of empathetic human-computer interaction systems. This paper presents a comparative analysis of lightweight transformer-based models, DistilHuBERT and PaSST, by classifying six core emotions from the CREMA-D dataset. We benchmark their performance against a traditional CNN-LSTM baseline model using MFCC features. DistilHuBERT demonstrates superior accuracy (70.64%) and F1 score (70.36%) while maintaining an exceptionally small model size (0.02 M… Open Article Page

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Explore Anomaly Detection W Topic Anomaly Detection arXiv (Cornell University) Emotion Detection in Speech Using Lightweight and Transformer-Based Models: A Comparative and Ablation Study 2025 Emotion recognition from speech plays a vital role in the development of empathetic human-computer interaction systems. This paper presents a comparative analysis of lightweight transformer-based models, DistilHuBERT and PaSST, by classifying six core emotion… Article Critical Symbolic Virtual Narrative Open Anomaly Detection Open Article Page