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Found 7 papers, 3 papers with code
Generating lyrics with variational autoencoder and multi-modal artist embeddings
We present a system for generating song lyrics lines conditioned on the style of a specified artist.
Disentangled Representation Learning for Non-Parallel Text Style Transfer
This paper tackles the problem of disentangling the latent variables of style and content in language models.
UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings
This paper describes the UWaterloo affect prediction system developed for EmoInt-2017.
UW-FinSent at SemEval-2017 Task 5: Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation
The system uses text vectorization models, such as N-gram, TF-IDF and paragraph embeddings, coupled with regression model variants to predict the sentiment scores.
Sentiment Analysis on Financial News Headlines using Training Dataset Augmentation
The system uses text vectorization models, such as N-gram, TF-IDF and paragraph embeddings, coupled with regression model variants to predict the sentiment scores.
A Survey of Neural Network Techniques for Feature Extraction from Text
This paper aims to catalyze the discussions about text feature extraction techniques using neural network architectures.
Rapid-Rate: A Framework for Semi-supervised Real-time Sentiment Trend Detection in Unstructured Big Data
Although such tasks like the one described about have been explored with respect to document classification problems in the past, the implementation described in this paper, by virtue of learning a continuous function rather than a discrete one, offers a lot more depth of insight as compared to document classification approaches.
