activity
20202025
most citedADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2025

Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis

Paul Mayer, Florian Lux, Alejandro Pérez-González-de-Martos +4

While generative methods have progressed rapidly in recent years, generating expressive prosody for an utterance remains a challenging task in text-to-speech synthesis. This is par…

cs.CL2024

Investigating the effect of Mental Models in User Interaction with an Adaptive Dialog Agent

Lindsey Vanderlyn, Dirk Väth, Ngoc Thang Vu

Mental models play an important role in whether user interaction with intelligent systems, such as dialog systems is successful or not. Adaptive dialog systems present the opportun…

cs.CL2024

Towards a Zero-Data, Controllable, Adaptive Dialog System

Dirk Väth, Lindsey Vanderlyn, Ngoc Thang Vu

Conversational Tree Search (Väth et al., 2023) is a recent approach to controllable dialog systems, where domain experts shape the behavior of a Reinforcement Learning agent throug…

cs.CL2023

Conversational Tree Search: A New Hybrid Dialog Task

Dirk Väth, Lindsey Vanderlyn, Ngoc Thang Vu

Conversational interfaces provide a flexible and easy way for users to seek information that may otherwise be difficult or inconvenient to obtain. However, existing interfaces gene…

cs.CL2020★ 1 cited

ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents

Chia-Yu Li, Daniel Ortega, Dirk Väth +9

We present ADVISER - an open-source, multi-domain dialog system toolkit that enables the development of multi-modal (incorporating speech, text and vision), socially-engaged (e.g.…