Papers by Mahsa Shafaei
Age Suitability Rating: Predicting the MPAA Rating Based on Movie Dialogues (2020.lrec-1)
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| Challenge: | Using the MPAA rating, movie content can negatively affect children’s behaviour, for example, watching specific programs may encourage irresponsible sexual behavior and alcohol usage in teenagers. |
| Approach: | They propose an RNN-based architecture that jointly models the genre and the emotions in the script to predict the MPAA rating. |
| Outcome: | The proposed model outperforms the traditional machine learning method by 7% and achieves an 81% weighted F1 score. |
From None to Severe: Predicting Severity in Movie Scripts (2021.findings-emnlp)
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| Challenge: | Existing rating systems only provide simple age restrictions and do not include suitability level on a specific aspect of the content. |
| Approach: | They propose to categorize ordinal severity of movies on 5 aspects using dialogue script data . they propose to use a siamese network-based multitask framework to improve interpretability . |
| Outcome: | The proposed method outperforms the state-of-the-art model and provides useful information to interpret predictions. |
ParsiNLU: A Suite of Language Understanding Challenges for Persian (2021.tacl-1)
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Daniel Khashabi, Arman Cohan, Siamak Shakeri, Pedram Hosseini, Pouya Pezeshkpour, Malihe Alikhani, Moin Aminnaseri, Marzieh Bitaab, Faeze Brahman, Sarik Ghazarian, Mozhdeh Gheini, Arman Kabiri, Rabeeh Karimi Mahabagdi, Omid Memarrast, Ahmadreza Mosallanezhad, Erfan Noury, Shahab Raji, Mohammad Sadegh Rasooli, Sepideh Sadeghi, Erfan Sadeqi Azer, Niloofar Safi Samghabadi, Mahsa Shafaei, Saber Sheybani, Ali Tazarv, Yadollah Yaghoobzadeh
| Challenge: | Despite progress in natural language understanding, most progress is concentrated on resource-rich languages like English . despite high-quality benchmarks, there are few available NLU datasets for Persian language . |
| Approach: | They propose a benchmark for Persian language that includes a range of language understanding tasks . they present their results on monolingual and multilingual pre-trained language models . |
| Outcome: | The proposed benchmarks compare human performance with monolingual and multilingual models on Persian language with high quality evaluation datasets. |
Positive and Risky Message Assessment for Music Products (2024.lrec-main)
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| Challenge: | a new approach to content assessment is needed to assess positive and potentially harmful messages in music. |
| Approach: | They propose a multi-task predictive model fortified with ordinality-enforcement to assess positive and potentially harmful messages within music products. |
| Outcome: | The proposed method outperforms task-specific alternatives and can assess multiple aspects simultaneously. |
Labeling Comic Mischief Content in Online Videos with a Multimodal Hierarchical-Cross-Attention Model (2024.lrec-main)
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| Challenge: | Existing systems for detecting questionable content in online media are limited by age, life experiences, socio-cultural values, and cognitive skills. |
| Approach: | They propose a multimodal system for comic mischief detection using video, text, and audio. |
| Outcome: | The proposed system improves existing models and baselines for comic mischief detection and its type classification. |