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Full-Text Articles in Physical Sciences and Mathematics
Turn Of Phrase: Contrastive Pre-Training For Discourse-Aware Conversation Models, Roland Laboulaye
Turn Of Phrase: Contrastive Pre-Training For Discourse-Aware Conversation Models, Roland Laboulaye
Theses and Dissertations
Understanding long conversations requires recognizing a discourse flow unique to conversation. Recent advances in unsupervised representation learning of text have been attained primarily through language modeling, which models discourse only implicitly and within a small window. These representations are in turn evaluated chiefly on sentence pair or paragraph-question pair benchmarks, which measure only local discourse coherence. In order to improve performance on discourse-reliant, long conversation tasks, we propose Turn-of-Phrase pre-training, an objective designed to encode long conversation discourse flow. We leverage tree-structured Reddit conversations in English to, relative to a chosen conversation path through the tree, select paths of varying …
Reinforcement Learning With Auxiliary Memory, Sterling Suggs
Reinforcement Learning With Auxiliary Memory, Sterling Suggs
Theses and Dissertations
Deep reinforcement learning algorithms typically require vast amounts of data to train to a useful level of performance. Each time new data is encountered, the network must inefficiently update all of its parameters. Auxiliary memory units can help deep neural networks train more efficiently by separating computation from storage, and providing a means to rapidly store and retrieve precise information. We present four deep reinforcement learning models augmented with external memory, and benchmark their performance on ten tasks from the Arcade Learning Environment. Our discussion and insights will be helpful for future RL researchers developing their own memory agents.
A Hybrid Method For Auralizing Vibroacoustic Systems And Evaluating Audio Fidelity/Sound Quality Using Machine Learning, Andrew Jared Miller
A Hybrid Method For Auralizing Vibroacoustic Systems And Evaluating Audio Fidelity/Sound Quality Using Machine Learning, Andrew Jared Miller
Theses and Dissertations
Two separate methods are presented to aid in the creation and evaluation of acoustic simulations. The first is a hybrid method that allows separate low and high-frequency acoustic responses to be combined into a single broadband response suitable for auralization. The process consists of four steps: 1) creating separate low-frequency and high-frequency responses of the system of interest, 2) interpolating between the two responses to get a single broadband magnitude response, 3) adding amplitude modulation to the high-frequency portion of the response, and 4) calculating approximate phase information. An experimental setup is used to validate the hybrid method. Listening tests …