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Chinese Idiom Understanding With Transformer-Based Pretrained Language Models, Minghuan Tan
Chinese Idiom Understanding With Transformer-Based Pretrained Language Models, Minghuan Tan
Dissertations and Theses Collection (Open Access)
In this dissertation, I study the understanding of Chinese idioms using transformer-based pretrained language models. By ``understanding", I confine the topics to word embeddings learning, contextualized word representations learning, multiple-choice cloze-test reading comprehension and conditional text generation. Chinese idioms are fixed phrases that have special meanings usually derived from an ancient story. The meanings of these idioms are oftentimes not directly related to their component characters, which makes it hard to model them compared with standard phrases whose meanings are compositional. We initiate the work with studying idiom representations derived from pretrained language models, in particular, BERT. We adopt probing-based …
Generating Music With Sentiments, Chunhui Bao
Generating Music With Sentiments, Chunhui Bao
Dissertations and Theses Collection (Open Access)
In this thesis, I focus on the music generation conditional on human sentiments such as positive and negative. As there are no existing large-scale music datasets annotated with sentiment labels, generating high-quality music conditioned on sentiments is hard. I thus build a new dataset consisting of the triplets of lyric, melody and sentiment, without requiring any manual annotations. I utilize an automated sentiment recognition model (based on the BERT trained on Edmonds Dance dataset) to "label'' the music according to the sentiments recognized from its lyrics. I then train the model of generating sentimental music and call the method Sentimental …
Music Popularity, Diffusion And Recommendation In Social Networks: A Fusion Analytics Approach, Jing Ren
Music Popularity, Diffusion And Recommendation In Social Networks: A Fusion Analytics Approach, Jing Ren
Dissertations and Theses Collection (Open Access)
Streaming music and social networks offer an easy way for people to gain access to a massive amount of music, but there are also challenges for the music industry to design for promotion strategies via the new channels. My dissertation employs a fusion of machine-based methods and explanatory empiricism to explore music popularity, diffusion, and promotion in the social network context.