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Persian Sentence-level Sentiment Polarity Classification
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In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03258138 ; ICOTEN, Jun 2021, Glasgow, United Kingdom (2021)
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Persian Sentence-level Sentiment Polarity Classification
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In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03241928 ; ICOTEN, May 2021, Glasgow, France (2021)
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Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis
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Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
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A novel context-aware multimodal framework for persian sentiment analysis
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Abstract:
Most recent works on sentiment analysis have exploited the text modality. However, millions of hours of video recordings posted on social media platforms everyday hold vital unstructured information that can be exploited to more effectively gauge public perception. Multimodal sentiment analysis offers an innovative solution to computationally understand and harvest sentiments from videos by contextually exploiting audio, visual and textual cues. In this paper, we, firstly, present a first of its kind Persian multimodal dataset comprising more than 800 utterances, as a benchmark resource for researchers to evaluate multimodal sentiment analysis approaches in Persian language. Secondly, we present a novel context-aware multimodal sentiment analysis framework, that simultaneously exploits acoustic, visual and textual cues to more accurately determine the expressed sentiment. We employ both decision-level (late) and feature-level (early) fusion methods to integrate affective cross-modal information. Experimental results demonstrate that the contextual integration of multimodal features such as textual, acoustic and visual features deliver better performance (91.39%) compared to unimodal features (89.24%).
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Keyword:
Multimodal sentiment analysis; Persian sentiment analysis
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URL: http://researchrepository.napier.ac.uk/Output/2800735 https://doi.org/10.1016/j.neucom.2021.02.020
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A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect
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A Semi-supervised Approach for Sentiment Analysis of Arab(ic+izi) Messages: Application to the Algerian Dialect
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A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis
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Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts
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CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement
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Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances
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Deep Neural Network Driven Binaural Audio Visual Speech Separation
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Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System
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A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks
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A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks ...
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Lip-reading driven deep learning approach for speech enhancement
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In: abs/1808.00046 ; 1 ; 10 (2019)
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A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks
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