Categories: FAANG

Modeling Spoken Information Queries for Virtual Assistants: Open Problems, Challenges and Opportunities

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…
AI Generated Robotic Content

Recent Posts

Statistical Methods for Evaluating LLM Performance

The large language model (LLM) has become a cornerstone of many AI applications.

8 hours ago

Getting started with computer use in Amazon Bedrock Agents

Computer use is a breakthrough capability from Anthropic that allows foundation models (FMs) to visually…

8 hours ago

OpenAI’s strategic gambit: The Agents SDK and why it changes everything for enterprise AI

OpenAI's new API and Agents SDK consolidate a previously fragmented complex ecosystem into a unified,…

9 hours ago

Under Trump, AI Scientists Are Told to Remove ‘Ideological Bias’ From Powerful Models

A directive from the National Institute of Standards and Technology eliminates mention of “AI safety”…

9 hours ago

Exploring Prediction Targets in Masked Pre-Training for Speech Foundation Models

Speech foundation models, such as HuBERT and its variants, are pre-trained on large amounts of…

1 day ago

How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team…

1 day ago