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Texas ScholarWorks was established to provide open, online access to the products of the University's research and scholarship, to preserve these works for future generations, to promote new models of scholarly communication, and to help deepen community understanding of the value of higher education.
UT Tower and campus image credit: Earl McGehee, CC-BY, https://www.flickr.com/photos/ejmc/7452145850
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Recent Submissions
Deep Learning Approach to Simultaneously Localize Acoustic Source and Receiver with a Single Room Impulse Response
(2024-04) Hanish, Rick; Haberman, Michael
This report proposes a method of simultaneously estimating the locations of an acoustic source and receiver in a three-dimensional shoe box-shaped room. We use a convolutional neural network-based model where the only input is a single room impulse response with reverberations. We also propose a method of handling the case of degeneracy using a small amount of information about the positions of the source and receiver relative to one another. In contrast to existing methods, we require no additional information or constraints. The model was shown to have effectively learned patterns in the room impulse response signal, achieving average error of 1.401 m which is shown to be better than a random guess. Although error was still large, we view this work as a proof-of-concept, and we expect that future modifications to the model architecture will improve accuracy substantially, and preprocessing the synthetic data used as the model's input would allow it to generalize better to real-world data sets.
Masters thesis recital (voice (soprano))
(1979-04-03) Schmidt, Karen Lee; Unable to determine,
If music be the food of love / Henry Purcell -- Wesendonck cycle / Richard Wagner -- Deux mélodies hébraïques / Maurice Ravel -- Mariam matrem / Anon. -- Arded, corazón / Luis de Narvaez -- Seǹora, se te olvidare / Anriquez de Valderrábono -- Gentil cavallero / Diego Pisador -- La mañana de Sant Juan / Alonso de Mudarra -- Confiado jilguerillo : from Acis y Galatea / Antonio Literes (with: Montague Smith, guitar ; Susie Peek, violin ; Shirley Blair, viola ; Judy Roberts, cello) -- Love's philosophy / Frederick Delius -- Vedic hymn : Dawn / Gustav Holst -- Orpheus with his lute / Ralph Vaughan Williams -- Love went a-riding / Frank Bridge.
Attacking ELECTRA-Small: Universal Adversarial Triggers for Reading Comprehension
(2023-12-14) Gupta, Alok
New question answering computer programs are pretty good at their job. They perform well when tested on certain datasets, like SQuAD (Rajpurkar et al., 2016) However, these datasets might not fully represent the challenges that come up in real-world situations where understanding what you're reading is important.Even the most advanced models can be affected by disruptions and adversarial text that is meant to decrease a model’s performance. In our paper, we gener- ate adversarial text examples to lower accuracy for the task of reading comprehension testing against the ELECTRA-Small model (Clark et al., 2020) trained on SQuAD. We suggest using a method called "beam search" to create what we call "universal triggers." We then test these triggers on different parts of the SQuAD dataset, with different vocabulary lists. The adversarial trig- gers produced by our beam search are able to effectively reduce a model’s accuracy on the SQuAD dataset by 33% for ’Why’ questions.