1 code implementation • 12 Oct 2023 • Foivos I. Diakogiannis, Suzanne Furby, Peter Caccetta, Xiaoliang Wu, Rodrigo Ibata, Ondrej Hlinka, John Taylor
By adding this "temporal" dimension, we exploit strong signal correlations between successive observations in the sequence to reduce error rates.
no code implementations • 29 May 2023 • Xiaoliang Wu, Peter Bell, Ajitha Rajan
Explainable AI (XAI) techniques have been widely used to help explain and understand the output of deep learning models in fields such as image classification and Natural Language Processing.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 27 Feb 2023 • Xiaoliang Wu, Peter Bell, Ajitha Rajan
We address quality assessment for neural network based ASR by providing explanations that help increase our understanding of the system and ultimately help build trust in the system.
Automatic Speech Recognition Explainable Artificial Intelligence (XAI) +4
no code implementations • 3 Dec 2021 • Xiaoliang Wu, Ajitha Rajan
We evaluate portability and effectiveness of our techniques using three popular ASRs and two input audio datasets using the metrics - Word Error Rate (WER) of output transcription, Similarity to original audio, attack Success Rate on different ASRs and Detection score by a defense system.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • 25 Sep 2020 • Xiaoliang Wu, Alexander Kolar, Joaquin Chung, Dong Jin, Tian Zhong, Rajkumar Kettimuthu, Martin Suchara
We implement a comprehensive suite of network protocols and demonstrate the use of SeQUeNCe by simulating a photonic quantum network with nine routers equipped with quantum memories.
Quantum Physics