# LD-SDS: Towards an Expressive Spoken Dialogue System based on Linked-Data

arXiv: https://arxiv.org/abs/1710.02973 · HTML: https://mlsanity.com/paper/1710.02973/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Oct 2017.

## Built on by (most cited first, 2 of 2)

- [ParaSpeechCLAP: A Dual-Encoder Speech-Text Model for Rich Stylistic Language-Audio Pretraining](https://mlsanity.com/paper/2603.28737/) (2026)
- [Open-domain Topic Identification of Out-of-domain Utterances using Wikipedia](https://mlsanity.com/paper/2101.11134/) (2021)

## Abstract (arXiv)

In this work we discuss the related challenges and describe an approach towards the fusion of state-of-the-art technologies from the Spoken Dialogue Systems (SDS) and the Semantic Web and Information Retrieval domains. We envision a dialogue system named LD-SDS that will support advanced, expressive, and engaging user requests, over multiple, complex, rich, and open-domain data sources that will leverage the wealth of the available Linked Data. Specifically, we focus on: a) improving the identification, disambiguation and linking of entities occurring in data sources and user input; b) offering advanced query services for exploiting the semantics of the data, with reasoning and exploratory capabilities; and c) expanding the typical information seeking dialogue model (slot filling) to better reflect real-world conversational search scenarios.