View publication

Virtual assistants are becoming increasingly important speech-driven Information Retrieval platforms that assist users with various tasks. We discuss open problems and challenges with respect to modeling spoken information queries for virtual assistants, and list opportunities where Information Retrieval methods and research can be applied to improve the quality of virtual assistant speech recognition. We discuss how query domain classification, knowledge graphs and user interaction data, and query personalization can be helpful in improving the accurate recognition of spoken information domain queries. Finally, we also provide a brief overview of current problems and challenges in speech recognition.

Related readings and updates.

International ACM Conference on Research and Development in Information Retrieval (SIGIR) 2023

Apple sponsored the International ACM Conference on Research and Development in Information Retrieval (SIGIR), which took place in a hybrid virtual and in-person format from July 23 to 27 in Taipei, Taiwan. SIGIR is an international forum focused on presenting new research in the information retrieval field. See below what was the accepted paper presentation schedule at SIGIR 2023.

See event details

Predicting Entity Popularity to Improve Spoken Entity Recognition by Virtual Assistants

We focus on improving the effectiveness of a Virtual Assistant (VA) in recognizing emerging entities in spoken queries. We introduce a method that uses historical user interactions to forecast which entities will gain in popularity and become trending, and it subsequently integrates the predictions within the Automated Speech Recognition (ASR) component of the VA. Experiments show that our proposed approach results in a 20% relative reduction in…
See paper details