Topological Data Analysis on Noisy Quantum Computers
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
An adaptive-control procedure is described which is intended to improve both acoustic analysis and linguistic decoding in automatic recognition of continuous speech by bringing into agreement data available at each of these stages. Specifically, hypotheses are formed by the decoder concerning the phonetic transcription derived during acoustic analysis. The procedure then accesses and utilizes relevant acoustic data in an attempt to verify or reject these hypotheses. Depending on the success of such attempts, actions are taken to constrain the decoding in subsequent processing iterations. Preliminary results are presented and discussed. © 1974.
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023
Hironori Takeuchi, Tetsuya Nasukawa, et al.
Transactions of the Japanese Society for Artificial Intelligence
Tim Erdmann, Stefan Zecevic, et al.
ACS Spring 2024