Agent-based Unsupervised Deep Interactive 0-shot-learning Networks Optimising Machines' Ontological Understanding of Sound (AUDI0NOMOUS)

音景是我们日常声学环境的一个组成部分；我们总是被声音包围，我们对它们做出反应，以及创造它们。虽然计算机试听，即机器对音频的理解，主要是通过分析语音来推动的，但对音景的理解却相对较少受到关注。AUDI0NOMOUS是一个基于人工智能系统的长期项目，旨在实现对现实生活音景的分析、分类和理解方面的重大突破。为了实现这一雄心勃勃的目标，本文提出了一种新的方法，基于开发四个高度协作和交互的智能代理。每个智能体都会自主地推断出对声音的深度和整体性理解。好奇代理将从网络资源和社交媒体收集独特的数据；音频分解代理将分解重叠的声音；学习代理将识别无限数量的未标记声音；本体论代理将把声音场景转换为口头本体。AUDI0NOMOUS将开启全面音频理解的全新维度；这些知识将对科学和人文学科产生高度和广泛的影响，促进医疗保健、机器人、智能设备和城市等领域的进步。

Soundscapes are a component of our everyday acoustic environment; we are always surrounded by sounds, we react to them, as well as creating them. While computer audition, the understanding of audio by machines, has primarily been driven through the analysis of speech, the understanding of soundscapes has received comparatively little attention. AUDI0NOMOUS, a long-term project based on artificial intelligent systems, aims to achieve a major breakthroughs in analysis, categorisation, and understanding of real-life soundscapes. A novel approach, based around the development of four highly cooperative and interactive intelligent agents, is proposed herein to achieve this highly ambitious goal. Each agent will autonomously infer a deep and holistic comprehension of sound. A Curious Agent will collect unique data from web sources and social media; an Audio Decomposition Agent will decompose overlapped sounds; a Learning Agent will recognise an unlimited number of unlabelled sound; and, an Ontology Agent will translate the soundscapes into verbal ontologies. AUDI0NOMOUS will open up an entirely new dimension of comprehensive audio understanding; such knowledge will have a high and broad impact in disciplines of both the sciences and humanities, promoting advancements in health care, robotics, and smart devices and cities, amongst many others.