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

ELOQUENCE - 用于安全关键应用的上下文感知和偏差控制对话系统的多语言和跨文化交互

• 批准号: 10092660
• 金额: $ 32.46万
• 依托单位: UNIVERSITY OF ESSEX
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10092660
• 关键词: ELOQUENCE; Multilingual; Cross; cultural; interactions

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.

EQUQUENCE专注于研究和开发协作语音/聊天机器人的创新技术。语音助理驱动的对话引擎以前已经部署在许多商业和政府技术管道中，具有不同的复杂程度。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。CQUENCE的主要目标是更好地理解这些非结构化的对话，并将其转换为可解释的，安全的，基于知识的，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主学习的技术，通过适应数据非常有限的语料库来有效地支持大多数欧盟语言;从可持续的计算框架到高效的绿色电力架构，从本质上讲，这可以作为所有欧洲公民的指导，同时尊重并展示我们欧洲最好的价值观，特别是通过参与人在环来支持安全关键应用。总的来说，CQQUENCE的项目考虑在会话代理领域的基础上建立并改进先前的成就，例如最近推出的公共领域大型语言模型（LLM），如chatGPT（例如，最近的版本），或LaMDa，其中大多数是在非欧盟国家开发的。虽然包括来自欧洲的主要工业企业（即，Omilia、Telefonica、Synelixis），EQUENCE将通过（i）安全关键应用程序的安全关键场景（即，呼叫中心中的紧急服务）和（ii）智能家庭助理通过信息检索和针对用于风险较小的自治系统的在线知识库的事实检查（即，家庭助理）。EQUENCE将在多语言和多模式环境中针对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。