Acoustic lexemes for organizing internet audio.
In this article, a method is proposed for automatic fine-scale audio description that draws inspiration from ontological sound description methods such as Shaeffer's Objets Sonores and Smalley's Spectromorphology . The goal is complete automation of audio description at the level of sound objects fo...
| Publicado en: | Contemporary Music Review Vol. 24; no. 6; pp. 489 - 509 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
2005
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=19019757&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 19019757 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 07494467 7VR jtl: Contemporary Music Review issn: 07494467 maglogo: N pubinfo: dt: 2005 vid: 24 iid: 6 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 19019757 10.1080/07494460500296169 ppf: 489 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.7MB tig: atl: Acoustic lexemes for organizing internet audio. aug: au: Casey, MichaelA. su: Computer sound processing Markov processes SQL Query languages (Computer science) ASCII (Character set) Character sets (Data processing) sug: subj: Computer sound processing Markov processes SQL Query languages (Computer science) ASCII (Character set) Character sets (Data processing) keyword: Acoustic Lexemes Audio Matching MPEG-7 Query Language Sound Object ab: In this article, a method is proposed for automatic fine-scale audio description that draws inspiration from ontological sound description methods such as Shaeffer's Objets Sonores and Smalley's Spectromorphology . The goal is complete automation of audio description at the level of sound objects for indexing and retrieving sound segments within Internet audio documents. To automatically segment audio documents into acoustic lexemes, a hidden Markov model is employed. It is demonstrated that the symbol stream of cluster labels, generated by the Viterbi algorithm, constitutes a detailed description of audio as a sequence of spectral archetypes. The ASCII base-64 encoding scheme maps cluster indices to one-character symbols that are segmented into 8-gram sequences for indexing in a relational database. To illustrate the methods, the essential components of an audio search engine are described: the automatic cataloguer, the retrieval engine and the query language. The results of experiments that test the accuracy and the retrieval efficiency of six new similarity-matching algorithms for audio using acoustic lexemes are presented. The article concludes with examples of audio matching using the structured query language (SQL) for creating new musical sequences from large extant audio collections. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Contemporary Music Review is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Contemporary Music Review holder: Taylor & Francis Ltd dt: @attributes: year: 2005 holdings: @attributes: islocal: N |
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