Natural Language Commanding via Program Synthesis
This addresses the challenge of enabling natural language interactions in productivity tools like Microsoft Office, though it appears incremental as it builds on existing LLM capabilities.
The authors tackled the problem of using natural language to command productivity software by introducing Semantic Interpreter, which translates user utterances into a domain-specific language for execution, achieving functional integration with Microsoft PowerPoint.
We present Semantic Interpreter, a natural language-friendly AI system for productivity software such as Microsoft Office that leverages large language models (LLMs) to execute user intent across application features. While LLMs are excellent at understanding user intent expressed as natural language, they are not sufficient for fulfilling application-specific user intent that requires more than text-to-text transformations. We therefore introduce the Office Domain Specific Language (ODSL), a concise, high-level language specialized for performing actions in and interacting with entities in Office applications. Semantic Interpreter leverages an Analysis-Retrieval prompt construction method with LLMs for program synthesis, translating natural language user utterances to ODSL programs that can be transpiled to application APIs and then executed. We focus our discussion primarily on a research exploration for Microsoft PowerPoint.