Exploring ASR-Free End-to-End Modeling to Improve Spoken Language Understanding in a Cloud-Based Dialog System
- Author(s):
- Qian, Yao; Ubale, Rutuja; Ramanarayanan, Vikram; Lange, Patrick; Suendermann-Oeft, David; Evanini, Keelan; Tsuprun, Eugene
- Patent Issued:
- Jan 11, 2022
- Patent Number:
- 11,222,627
- Source:
- ETS Patent
- Document Type:
- Patent
- Family ID:
- 79169262
- Subject/Key Words:
- Patent, Active Patent, Spoken Dialog System (SDS), Simulation Exercises, Audio Data, Language Learning
Abstract
Systems and methods are provided for conducting a simulated conversation with a language learner include determining a first dialog state of the simulated conversation. First audio data corresponding to simulated speech based on the dialog state is transmitted. Second audio data corresponding to a variable length utterance spoken in response to the simulated speech is received. A fixed dimension vector is generated based on the variable length utterance. A semantic label is predicted for the variable-length utterance based on the fixed dimension vector. A second dialog state of the simulated conversation is determined based on the semantic label, and third audio data corresponding to simulated speech is transmitted based on the second dialog state.