English-Malay Cross-Lingual Emotion Detection In Tweets Using Word Embedding Alignment
The three-phase methodology to address the goals of this study included the construction of the English-Malay cross-lingual word embedding using word embedding alignment, enrichment of the cross-lingual word embedding with sentiment information, and pre-training of the hierarchical attention model s...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2023
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.usm.my/60433/1/Pages%20from%20LIM%20YING%20HAO%20-%20TESIS.pdf |
| الوسوم: |
إضافة وسم
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| الملخص: | The three-phase methodology to address the goals of this study included the construction of the English-Malay cross-lingual word embedding using word embedding alignment, enrichment of the cross-lingual word embedding with sentiment information, and pre-training of the hierarchical attention model solely on English tweets. We evaluated our model in two scenarios: zero-shot learning and few-shot learning on 4176 Malay tweets annotated with emotion. We also examined the optimal number of Malay tweets required to finetune the model and the effect of finetuning different layers in our model. |
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