Search Results for author: Ishwarya Ananthabhotla

Found 5 papers, 1 papers with code

On HRTF Notch Frequency Prediction Using Anthropometric Features and Neural Networks

no code implementations12 Mar 2024 Lior Arbel, Ishwarya Ananthabhotla, Zamir Ben-Hur, David Lou Alon, Boaz Rafaely

High fidelity spatial audio often performs better when produced using a personalized head-related transfer function (HRTF).

Hearing Loss Detection from Facial Expressions in One-on-one Conversations

no code implementations17 Jan 2024 Yufeng Yin, Ishwarya Ananthabhotla, Vamsi Krishna Ithapu, Stavros Petridis, Yu-Hsiang Wu, Christi Miller

In this work, we build on this idea and introduce the problem of detecting hearing loss from an individual's facial expressions during a conversation.

Representation Learning

The Audio-Visual Conversational Graph: From an Egocentric-Exocentric Perspective

no code implementations20 Dec 2023 Wenqi Jia, Miao Liu, Hao Jiang, Ishwarya Ananthabhotla, James M. Rehg, Vamsi Krishna Ithapu, Ruohan Gao

We propose a unified multi-modal framework -- Audio-Visual Conversational Attention (AV-CONV), for the joint prediction of conversation behaviors -- speaking and listening -- for both the camera wearer as well as all other social partners present in the egocentric video.

Towards Improved Room Impulse Response Estimation for Speech Recognition

no code implementations8 Nov 2022 Anton Ratnarajah, Ishwarya Ananthabhotla, Vamsi Krishna Ithapu, Pablo Hoffmann, Dinesh Manocha, Paul Calamia

We propose a novel approach for blind room impulse response (RIR) estimation systems in the context of a downstream application scenario, far-field automatic speech recognition (ASR).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

HCU400: An Annotated Dataset for Exploring Aural Phenomenology Through Causal Uncertainty

1 code implementation15 Nov 2018 Ishwarya Ananthabhotla, David B. Ramsay, Joseph A. Paradiso

The way we perceive a sound depends on many aspects-- its ecological frequency, acoustic features, typicality, and most notably, its identified source.

Word Embeddings

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