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Found 7 papers, 5 papers with code
Interactive Assignments for Teaching Structured Neural NLP
We present a set of assignments for a graduate-level NLP course.
An Improved Model for Voicing Silent Speech
In this paper, we present an improved model for voicing silent speech, where audio is synthesized from facial electromyography (EMG) signals.
Overcoming Conflicting Data when Updating a Neural Semantic Parser
In this paper, we explore how to use a small amount of new data to update a task-oriented semantic parsing model when the desired output for some examples has changed.
Digital Voicing of Silent Speech
In this paper, we consider the task of digitally voicing silent speech, where silently mouthed words are converted to audible speech based on electromyography (EMG) sensor measurements that capture muscle impulses.
Pre-Learning Environment Representations for Data-Efficient Neural Instruction Following
We consider the problem of learning to map from natural language instructions to state transitions (actions) in a data-efficient manner.
What's Going On in Neural Constituency Parsers? An Analysis
A number of differences have emerged between modern and classic approaches to constituency parsing in recent years, with structural components like grammars and feature-rich lexicons becoming less central while recurrent neural network representations rise in popularity.
