12 citations · 34 across the 16 of their papers we have counts for
5 papers · 1 filter
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning
Liam Collins, Shanshan Wu, Sewoong Oh +1
In many applications of federated learning (FL), clients desire models that are personalized using their local data, yet are also robust in the sense that they retain general globa…
Contextual Biasing with the Knuth-Morris-Pratt Matching Algorithm
Weiran Wang, Zelin Wu, Diamantino Caseiro +10
Contextual biasing refers to the problem of biasing the automatic speech recognition (ASR) systems towards rare entities that are relevant to the specific user or application scena…
Massive End-to-end Models for Short Search Queries
Weiran Wang, Rohit Prabhavalkar, Dongseong Hwang +11
In this work, we investigate two popular end-to-end automatic speech recognition (ASR) models, namely Connectionist Temporal Classification (CTC) and RNN-Transducer (RNN-T), for of…
Improving Speech Recognition for African American English With Audio Classification
Shefali Garg, Zhouyuan Huo, Khe Chai Sim +11
Automatic speech recognition (ASR) systems have been shown to have large quality disparities between the language varieties they are intended or expected to recognize. One way to m…
Edit Distance based RL for RNNT decoding
Dongseong Hwang, Changwan Ryu, Khe Chai Sim
RNN-T is currently considered the industry standard in ASR due to its exceptional WERs in various benchmark tests and its ability to support seamless streaming and longform transcr…