| Paper ID | ASPS-5.6 |
| Paper Title |
GRAPH ENHANCED QUERY REWRITING FOR SPOKEN LANGUAGE UNDERSTANDING SYSTEM |
| Authors |
Siyang Yuan, Duke University, United States; Saurabh Gupta, Xing Fan, Derek Liu, Yang Liu, Chenlei Guo, Amazon.com, Inc., United States |
| Session | ASPS-5: Audio & Images |
| Location | Gather.Town |
| Session Time: | Thursday, 10 June, 16:30 - 17:15 |
| Presentation Time: | Thursday, 10 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Applied Signal Processing Systems: Signal Processing Systems [DIS-EMSA] |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Query rewriting (QR) is an increasingly important component in voice assistant systems to reduce customer friction caused by errors in a spoken language understanding pipeline. These errors originate from various sources such as Automatic Speech Recognition (ASR) and Natural Language Understanding (NLU) modules. In this work, we construct a user interaction graph from their queries using data mined from a Markov Chain Model, and introduce a self-supervised pre-training process for learning query embeddings by leveraging the recent developments in Graph Representation Learning (GRL). We then fine-tune these embeddings with weak supervised data for the query rewriting task, and observe improvement over the neural retrieval baseline system, which demonstrates the effectiveness of the proposed method. |
