ELOQUENCE - Multilingual and Cross-cultural interactions for context-aware, and bias-controlled dialogue systems for safety-critical applications

Eloquence专注于研究和开发协作语音/聊天机器人的创新技术。语音助手驱动的对话引擎以前曾被部署在许多商业和政府技术管道中，具有不同程度的复杂性。在我们的概念中，这种复杂性可以理解为分析非结构化对话的问题。口才的主要目标是更好地理解这些非结构化的对话，并将它们翻译成可解释的、安全的、知识全面的、值得信赖的和偏见控制的语言模型。我们设想开发一种能够自行学习的技术，方法是从非常有限的数据语料库进行调整，以有效支持大多数欧盟语言；从可持续的计算框架到高效和绿色能源的架构，本质上，这可以作为所有欧洲公民的指南，同时尊重并展示我们最好的欧洲价值观，特别是通过让人在循环中参与来支持安全关键型应用程序。总体而言，Eloquence的项目考虑在会话代理领域的先前成就的基础上发展和改进，例如最近推出的和公共领域的大型语言模型(LLM)，如chat GPT(例如，较新的版本)或Lamda，其中大多数是在非欧盟国家开发的。在包括来自欧洲的主要工业企业(即Omilia、Telefonica、Synelixis)的同时，雄辩将通过(I)针对安全关键应用(即呼叫中心的紧急服务)的人在回路中的安全关键场景和(Ii)通过针对风险较小的自主系统(即家庭助理)的在线知识库进行信息检索和事实核查来验证所开发的技术。雄辩将针对多语言和多模式环境中这些新型对话式人工智能技术的研发，并在几个试点中进行演示。

ELOQUENCE is focused on the research and development of innovative technologies for collaborative voice/chat bots. Voice assistantpowered dialogue engines have previously been deployed in a number of commercial and governmental technological pipelines, with a diverse level of complexity. In our concept, such a complexity can be understood as a problem of analysing unstructured dialogues. ELOQUENCE’s key objective isto better comprehend those unstructured dialogues and translate them into explainable,safe, knowledgegrounded, trustworthy and bias-controlled language models. We envision to develop a technology capable of learning by its own, by adapting from a very data-limited corpora to efficiently support most of the EU languages; from a sustainable computational framework to efficient and green-power architectures and, in essence, that may serve as a guidance for all European citizens whilst being respectful and showing the best of our European values, specifically supporting safety-critical applications by involving humans-in-the-loop. Overall, ELOQUENCE’s project considers building on top and to improve of prior achievements in the domain of conversational agents, e.g. recently launched and public-domain Large Language Models (LLMs), such as chatGPT (e.g., more recent versions), or LaMDa most of them developed in non-EU countries. While including key industrial enterprises from Europe (i.e., Omilia, Telefonica, Synelixis), ELOQUENCE will validate the developed technology through (i) safety-critical scenarios with human-in-the-loop for security-critical applications (i.e., emergency services in call centres) and (ii) smart home assistants via information retrieval and fact-checking against an online knowledge base for lesser risky autonomous systems (i.e., home-assistants). ELOQUENCE will target the R&D of these novel conversational AI technologies in multilingual and multimodal environments and demonstrated in several pilots.