Pub Date : 1900-01-01DOI: 10.4324/9780203059746-13
R. Rowe
{"title":"Interactive Music Systems in Ensemble Performance","authors":"R. Rowe","doi":"10.4324/9780203059746-13","DOIUrl":"https://doi.org/10.4324/9780203059746-13","url":null,"abstract":"","PeriodicalId":121121,"journal":{"name":"Readings in Music and Artificial Intelligence","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121331835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we introduce the idea of Knowledge Representation in the context of Artificial Intelligence. We explain why finding a good representation is an important issue in Artificial Intelligence research, and why music raises some particularly interesting questions. We then proceed to explain our own system for music knowledge representation, Charm.
{"title":"Musical Knowledge: What can Artificial Intelligence Bring to the Musician?","authors":"Geraint A. Wiggins, A. Smaill","doi":"10.4324/9780203059746-8","DOIUrl":"https://doi.org/10.4324/9780203059746-8","url":null,"abstract":"In this paper we introduce the idea of Knowledge Representation in the context of Artificial Intelligence. We explain why finding a good representation is an important issue in Artificial Intelligence research, and why music raises some particularly interesting questions. We then proceed to explain our own system for music knowledge representation, Charm.","PeriodicalId":121121,"journal":{"name":"Readings in Music and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131048917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In cognitive science and research on artificial intelligence, there are two central paradigms: the symbolic and the analogical. Within the analogical paradigm, interest in artificial neural networks, or connectionism, has experienced a resurgence during the last decade; this change has also been reflected in the field of musical modeling. This article provides a general survey of the relationship between symbolic AI and connectionism, both on a general level and from the point of view of music research. This is followed by a short introduction to artificial neural networks, which includes a description the main principles of their structure and function as well as a presentation examples of their use in the field of music.
{"title":"Symbolic AI versus Connectionism in Music Research","authors":"P. Toiviainen","doi":"10.4324/9780203059746-9","DOIUrl":"https://doi.org/10.4324/9780203059746-9","url":null,"abstract":"In cognitive science and research on artificial intelligence, there are two central paradigms: the symbolic and the analogical. Within the analogical paradigm, interest in artificial neural networks, or connectionism, has experienced a resurgence during the last decade; this change has also been reflected in the field of musical modeling. This article provides a general survey of the relationship between symbolic AI and connectionism, both on a general level and from the point of view of music research. This is followed by a short introduction to artificial neural networks, which includes a description the main principles of their structure and function as well as a presentation examples of their use in the field of music.","PeriodicalId":121121,"journal":{"name":"Readings in Music and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123164523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The discipline of Music-AI is defined as that activity which seeks to program computers to perform musical tasks in an intelligent, which possibly means humanlike way. A brief historical survey of different approaches within the discipline is presented. Two particular issues arise: the explicit representation of knowledge; and symbolic and subsymbolic representation and processing. When attempting to give a precise definition of Music-AI, it is argued that all musical processes must make some reference to human behaviour, and so Music-AI is a central rather than a peripheral discipline for musical computing. However, it turns out that the goals of Music-AI as first expressed, the mimicking of human behaviour, are impossible to achieve in full, and that it is impossible, in principle, for computers to pass a musical version of the Turing test. In practice, however, computers are used for their non-human-like behaviour just as much as their human-like behaviour, so the real goal of Music-AI must be reformulated. Furthermore, it is argued that the non-holistic analysis of human behaviour which this reformulation entails is actually informative for our understanding of human behaviour. Music-AI could also be fruitfully concerned with developing musical intelligences which were explicitly not human. Music-AI is then seen to be as much a creative enterprise as a scientific one.
{"title":"Music, Intelligence and Artificiality","authors":"A. Marsden","doi":"10.4324/9780203059746-7","DOIUrl":"https://doi.org/10.4324/9780203059746-7","url":null,"abstract":"The discipline of Music-AI is defined as that activity which seeks to program computers to perform musical tasks in an intelligent, which possibly means humanlike way. A brief historical survey of different approaches within the discipline is presented. Two particular issues arise: the explicit representation of knowledge; and symbolic and subsymbolic representation and processing. When attempting to give a precise definition of Music-AI, it is argued that all musical processes must make some reference to human behaviour, and so Music-AI is a central rather than a peripheral discipline for musical computing. However, it turns out that the goals of Music-AI as first expressed, the mimicking of human behaviour, are impossible to achieve in full, and that it is impossible, in principle, for computers to pass a musical version of the Turing test. In practice, however, computers are used for their non-human-like behaviour just as much as their human-like behaviour, so the real goal of Music-AI must be reformulated. Furthermore, it is argued that the non-holistic analysis of human behaviour which this reformulation entails is actually informative for our understanding of human behaviour. Music-AI could also be fruitfully concerned with developing musical intelligences which were explicitly not human. Music-AI is then seen to be as much a creative enterprise as a scientific one.","PeriodicalId":121121,"journal":{"name":"Readings in Music and Artificial Intelligence","volume":"346 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124272936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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