no code implementations • 27 Apr 2024 • Tiantian Feng, Xuan Shi, Rahul Gupta, Shrikanth S. Narayanan
Automatic Speech Understanding (ASU) aims at human-like speech interpretation, providing nuanced intent, emotion, sentiment, and content understanding from speech and language (text) content conveyed in speech.
no code implementations • 21 Mar 2024 • Alice Baird, Rachel Manzelli, Panagiotis Tzirakis, Chris Gagne, Haoqi Li, Sadie Allen, Sander Dieleman, Brian Kulis, Shrikanth S. Narayanan, Alan Cowen
In this short white paper, to encourage researchers with limited access to large-datasets, the organizers first outline several open-source datasets that are available to the community, and for the duration of the workshop are making several propriety datasets available.
1 code implementation • 29 Sep 2023 • Samiul Alam, Tuo Zhang, Tiantian Feng, Hui Shen, Zhichao Cao, Dong Zhao, JeongGil Ko, Kiran Somasundaram, Shrikanth S. Narayanan, Salman Avestimehr, Mi Zhang
However, most existing FL works are not conducted on datasets collected from authentic IoT devices that capture unique modalities and inherent challenges of IoT data.
1 code implementation • 3 Jun 2023 • Tuo Zhang, Tiantian Feng, Samiul Alam, Dimitrios Dimitriadis, Mi Zhang, Shrikanth S. Narayanan, Salman Avestimehr
Through comprehensive ablation analysis, we discover that the downstream model generated by synthetic data plays a crucial role in controlling the direction of gradient diversity during FL training, which enhances convergence speed and contributes to the notable accuracy boost observed with GPT-FL.
1 code implementation • 26 Dec 2021 • Tiantian Feng, Hanieh Hashemi, Rajat Hebbar, Murali Annavaram, Shrikanth S. Narayanan
To assess the information leakage of SER systems trained using FL, we propose an attribute inference attack framework that infers sensitive attribute information of the clients from shared gradients or model parameters, corresponding to the FedSGD and the FedAvg training algorithms, respectively.
no code implementations • 14 Feb 2021 • Yongwan Lim, Shrikanth S. Narayanan, Krishna S. Nayak
Spiral acquisitions are preferred in real-time MRI because of their efficiency, which has made it possible to capture vocal tract dynamics during natural speech.