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Found 11 papers, 2 papers with code
Does BERT Know that the IS-A Relation Is Transitive?
The success of a natural language processing (NLP) system on a task does not amount to fully understanding the complexity of the task, typified by many deep learning models.
System Combination for Grammatical Error Correction Based on Integer Programming
In this paper, we propose a system combination method for grammatical error correction (GEC), based on nonlinear integer programming (IP).
The black hole of logistics costs of digitizing commodity money
We proved that there is not such honest money from the perspective of logistics costs, which is both the store of value like precious metal and without logistics costs in circulation like digital currency.
Improved Robust ASR for Social Robots in Public Spaces
Social robots deployed in public spaces present a challenging task for ASR because of a variety of factors, including noise SNR of 20 to 5 dB.
Multi-Layer Ensembling Techniques for Multilingual Intent Classification
In this paper we determine how multi-layer ensembling improves performance on multilingual intent classification.
Combining Word Feature Vector Method with the Convolutional Neural Network for Slot Filling in Spoken Language Understanding
Slot filling is an important problem in Spoken Language Understanding (SLU) and Natural Language Processing (NLP), which involves identifying a user's intent and assigning a semantic concept to each word in a sentence.
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques
The challenge for Chinese intent classification stems from the fact that, unlike English where most words are made up of 26 phonologic alphabet letters, Chinese is logographic, where a Chinese character is a more basic semantic unit that can be informative and its meaning does not vary too much in contexts.
Zara: A Virtual Interactive Dialogue System Incorporating Emotion, Sentiment and Personality Recognition
Zara, or {`}Zara the Supergirl{'} is a virtual robot, that can exhibit empathy while interacting with an user, with the aid of its built in facial and emotion recognition, sentiment analysis, and speech module.
Sentiment Classification of Food Reviews
In this work, the goal is to predict the score of food reviews on a scale of 1 to 5 with two recurrent neural networks that are carefully tuned.
Towards Empathetic Human-Robot Interactions
Although research on empathetic robots is still in the early stage, we described our approach using signal processing techniques, sentiment analysis and machine learning algorithms to make robots that can "understand" human emotion.
