Výsledky vyhledávání - "Ishwarya Ananthabhotla"

Cognitive Audio Interfaces: Mediating Sonic Information With an Understanding of How We Hear

Autor: David B. Ramsay, Joseph A. Paradiso, Ishwarya Ananthabhotla, Clement Duhart

Publikováno v: IEEE Pervasive Computing. 20:36-45

In a world of rich, complex, and demanding audio environments, intelligent systems can mediate our interaction with the sounds around us—both to enable meaningful, aesthetic experiences and to transition work from humans to computational agents. Dr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d41d951a6b04723f6da193991250e3c6
https://doi.org/10.1109/mprv.2021.3052659

Zobrazit plný text záznamu

Manipulating Causal Uncertainty in Sound Objects

Autor: Joseph A. Paradiso, Tal Boger, Ishwarya Ananthabhotla

Publikováno v: Audio Mostly Conference

Causal uncertainty – how sure we are in what produced a sound that we are listening to – is a fundamental aspect of auditory cognition. It is known to be a driver of affect perception, attention, and memory, among other processes. Here, we presen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3bb7e74d6416bcf4e6b4f5b75c471e32
https://doi.org/10.1145/3478384.3478405

Zobrazit plný text záznamu

ATHack: Co-Design and Education in Assistive Technology Development

Autor: Cameron Taylor, Hosea Siu, Adriana Mallozzi, Samuel Mendez, Jaya Narain, Ishwarya Ananthabhotla, Lora Brugnaro

Publikováno v: CHI Extended Abstracts

ATHack, an annual assistive technologies hackathon at MIT, is unique in that community members living with disabilities (co-designers) propose projects and work with hackers to create prototypes over a two-week period. Since 2014, over 75 co-designer

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dd8ed83b52f8d8e9f75c1f8f51503bbd
https://doi.org/10.1145/3334480.3383096

Zobrazit plný text záznamu

Using a Neural Network Codec Approximation Loss to Improve Source Separation Performance in Limited Capacity Networks

Autor: Sebastian Ewert, Joseph A. Paradiso, Ishwarya Ananthabhotla

Publikováno v: MIT web domain
IJCNN

© 2020 IEEE. A growing need for on-device machine learning has led to an increased interest in light-weight neural networks that lower model complexity while retaining performance. While a variety of general-purpose techniques exist in this context,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a90a4ae00eb73450c62e99a467818ba
https://hdl.handle.net/1721.1/137109

Zobrazit plný text záznamu

HCU400: an Annotated Dataset for Exploring Aural Phenomenology through Causal Uncertainty

Autor: David B. Ramsay, Joseph A. Paradiso, Ishwarya Ananthabhotla

Publikováno v: ICASSP
arXiv

© 2019 IEEE. The way we perceive a sound depends on many aspects- its ecological frequency, acoustic features, typicality, and most notably, its identified source. In this paper, we present the HCU400: a dataset of 402 sounds ranging from easily ide

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e9c9d6d4baade8792c42d03966efdef
https://doi.org/10.1109/icassp.2019.8683147

Zobrazit plný text záznamu

A framework for designing head-related transfer function distance metrics that capture localization perception

Autor: W. Owen Brimijoin, Vamsi K. Ithapu, Ishwarya Ananthabhotla

Publikováno v: JASA Express Letters. 1:044401

Linear comparisons can fail to describe perceptual differences between head-related transfer functions (HRTFs), reducing their utility for perceptual tests, HRTF selection methods, and prediction algorithms. This work introduces a machine learning fr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b380aba2e1d2cf4697796f422df4661b
https://doi.org/10.1121/10.0003983

Zobrazit plný text záznamu

Towards a Perceptual Loss: Using a Neural Network Codec Approximation as a Loss for Generative Audio Models

Autor: Ishwarya Ananthabhotla, Joseph A. Paradiso, Sebastian Ewert

Publikováno v: MIT web domain
ACM Multimedia

© 2019 Association for Computing Machinery. Generative audio models based on neural networks have led to considerable improvements across fields including speech enhancement, source separation, and text-to-speech synthesis. These systems are typical

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::670f334dbe9e24375ba3ecbf927494b6
https://hdl.handle.net/1721.1/137115

Zobrazit plný text záznamu

MIT Community Challenge

Autor: Rosalind W. Picard, Alexandra Rieger, Ishwarya Ananthabhotla, Dan Greenberg

Publikováno v: CHI Extended Abstracts

The MIT Community Challenge is a project created in response to mental health and wellbeing concerns on MIT's campus. Surveys given by the chancellor indicate that students at MIT feel that the academic environment negatively impacts their wellbeing

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::65ec1c9e5f179c798a0dfb8f176bb653
https://doi.org/10.1145/3027063.3053208

Zobrazit plný text záznamu

Folding Angle Regulation by Curved Crease Design for Self-Assembling Origami Propellers

Autor: Ishwarya Ananthabhotla, Byoungkwon An, Daniela Rus, Shuhei Miyashita, Isabella DiDio, Slava Arabagi, Cynthia Sung

Publikováno v: Journal of Mechanisms and Robotics. 7

This paper describes a method for manufacturing complex three-dimensional curved structures by self-folding layered materials. Our main focus is to first show that the material can cope with curved crease self-folding and then to utilize the curvatur

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ff322ac7398e29f86423ac0e55b2727b
https://doi.org/10.1115/1.4029548

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání