Efficient Index-Based Audio Matching
Identifieur interne : 000011 ( PascalFrancis/Corpus ); précédent : 000010; suivant : 000012Efficient Index-Based Audio Matching
Auteurs : Frank Kurth ; Meinard MüllerSource :
- IEEE transactions on audio, speech and language processing [ 1558-7916 ] ; 2008.
Descripteurs français
- Pascal (Inist)
- Base de données audio, Document musical, Enregistrement son, Identification système, Immunité bruit, Traitement signal audio, Compression signal, Artefact, Similitude, Requête, Présentation de la ligne apellante, Base de données, Analyse sémantique, Algorithme, Tolérance faute, Indexation, Traitement signal acoustique, Présentation ligne appelante.
English descriptors
- KwdEn :
Abstract
Given a large audio database of music recordings, the goal of classical audio identification is to identify a particular audio recording by means of a short audio fragment. Even though recent identification algorithms show a significant degree of robustness towards noise, MP3 compression artifacts, and uniform temporal distortions, the notion of similarity is rather close to the identity. In this paper, we address a higher level retrieval problem, which we refer to as audio matching: given a short query audio clip, the goal is to automatically retrieve all excerpts from all recordings within the database that musically correspond to the query. In our matching scenario, opposed to classical audio identification, we allow semantically motivated variations as they typically occur in different Interpretations of a piece of music. To this end, this paper presents an efficient and robust audio matching procedure that works even in the presence of significant variations, such as nonlinear temporal, dynamical, and spectral deviations, where existing algorithms for audio identification would fail. Furthermore, the combination of various deformation- and fault-tolerance mechanisms allows us to employ standard indexing techniques to obtain an efficient, index-based matching procedure, thus providing an important step towards semantically searching large-scale real-world music collections.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
| pA |
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|---|
Format Inist (serveur)
| NO : | PASCAL 08-0185407 INIST |
|---|---|
| FT : | Music Information Retrieval |
| ET : | Efficient Index-Based Audio Matching |
| AU : | KURTH (Frank); MÜLLER (Meinard); SLANEY (Malcolm); ELLIS (Daniel P. W.); SANDLER (Mark); GOTO (Masataka); GOODWIN (Michael M.) |
| AF : | Research Institute for Communication, Information Processing and Ergonomics (FKIE), Research Establishment for Applied Scenice (FGAN)/53343 Wachtberg/Allemagne (1 aut.); Max-Planck Institut für Informatik, Department D4-Computer Graphics/66123 Saarbrücken/Allemagne (2 aut.); Yahoo! Research Labs and Stanford University CCRMA/Santa Clara, CA 95054/Etats-Unis (1 aut.); Columbia University/New York, NY 10027-6902/Etats-Unis (2 aut.); Queen Mary, University of London/London, E1 4NS/Royaume-Uni (3 aut.); National Institute of Advanced Industrial Science and Technology (AIST)/Tsukuba, 305-8568/Japon (4 aut.); Creative Advanced Technology Center/Scotts Valley, CA 95066/Etats-Unis (5 aut.) |
| DT : | Publication en série; Niveau analytique |
| SO : | IEEE transactions on audio, speech and language processing; ISSN 1558-7916; Etats-Unis; Da. 2008; Vol. 16; No. 2; Pp. 382-395; Bibl. 38 ref. |
| LA : | Anglais |
| EA : | Given a large audio database of music recordings, the goal of classical audio identification is to identify a particular audio recording by means of a short audio fragment. Even though recent identification algorithms show a significant degree of robustness towards noise, MP3 compression artifacts, and uniform temporal distortions, the notion of similarity is rather close to the identity. In this paper, we address a higher level retrieval problem, which we refer to as audio matching: given a short query audio clip, the goal is to automatically retrieve all excerpts from all recordings within the database that musically correspond to the query. In our matching scenario, opposed to classical audio identification, we allow semantically motivated variations as they typically occur in different Interpretations of a piece of music. To this end, this paper presents an efficient and robust audio matching procedure that works even in the presence of significant variations, such as nonlinear temporal, dynamical, and spectral deviations, where existing algorithms for audio identification would fail. Furthermore, the combination of various deformation- and fault-tolerance mechanisms allows us to employ standard indexing techniques to obtain an efficient, index-based matching procedure, thus providing an important step towards semantically searching large-scale real-world music collections. |
| CC : | 001D04A04A2; 001D04A05D |
| FD : | Base de données audio; Document musical; Enregistrement son; Identification système; Immunité bruit; Traitement signal audio; Compression signal; Artefact; Similitude; Requête; Présentation de la ligne apellante; Base de données; Analyse sémantique; Algorithme; Tolérance faute; Indexation; Traitement signal acoustique; Présentation ligne appelante |
| ED : | Audio databases; Musical score; Sound recording; System identification; Noise immunity; Audio signal processing; Signal compression; Artefact; Similarity; Query; Calling line identification presentation; Database; Semantic analysis; Algorithm; Fault tolerance; Indexing; Acoustic signal processing; Calling line identification presentation |
| SD : | Documento musical; Registro sonido; Identificación sistema; Inmunidad ruido; Compresión señal; Artefacto; Similitud; Pregunta documental; Identificación de llamada entrante; Base dato; Análisis semántico; Algoritmo; Tolerancia falta; Indización |
| LO : | INIST-26266.354000183429570120 |
| ID : | 08-0185407 |
Links to Exploration step
Pascal:08-0185407Le document en format XML
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Even though recent identification algorithms show a significant degree of robustness towards noise, MP3 compression artifacts, and uniform temporal distortions, the notion of similarity is rather close to the identity. In this paper, we address a higher level retrieval problem, which we refer to as audio matching: given a short query audio clip, the goal is to automatically retrieve all excerpts from all recordings within the database that musically correspond to the query. In our matching scenario, opposed to classical audio identification, we allow semantically motivated variations as they typically occur in different Interpretations of a piece of music. To this end, this paper presents an efficient and robust audio matching procedure that works even in the presence of significant variations, such as nonlinear temporal, dynamical, and spectral deviations, where existing algorithms for audio identification would fail. Furthermore, the combination of various deformation- and fault-tolerance mechanisms allows us to employ standard indexing techniques to obtain an efficient, index-based matching procedure, thus providing an important step towards semantically searching large-scale real-world music collections.</div></front></TEI><inist><standard h6="B"><pA><fA01 i1="01" i2="2"><s0>1558-7916</s0></fA01><fA05><s2>16</s2></fA05><fA06><s2>2</s2></fA06><fA08 i1="01" i2="1" l="ENG"><s1>Efficient Index-Based Audio Matching</s1></fA08><fA09 i1="01" i2="1" l="FRE"><s1>Music Information Retrieval</s1></fA09><fA11 i1="01" i2="1"><s1>KURTH (Frank)</s1></fA11><fA11 i1="02" i2="1"><s1>MÜLLER (Meinard)</s1></fA11><fA12 i1="01" i2="1"><s1>SLANEY (Malcolm)</s1><s9>ed.</s9></fA12><fA12 i1="02" i2="1"><s1>ELLIS (Daniel P. 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W.); SANDLER (Mark); GOTO (Masataka); GOODWIN (Michael M.)</AU><AF>Research Institute for Communication, Information Processing and Ergonomics (FKIE), Research Establishment for Applied Scenice (FGAN)/53343 Wachtberg/Allemagne (1 aut.); Max-Planck Institut für Informatik, Department D4-Computer Graphics/66123 Saarbrücken/Allemagne (2 aut.); Yahoo! Research Labs and Stanford University CCRMA/Santa Clara, CA 95054/Etats-Unis (1 aut.); Columbia University/New York, NY 10027-6902/Etats-Unis (2 aut.); Queen Mary, University of London/London, E1 4NS/Royaume-Uni (3 aut.); National Institute of Advanced Industrial Science and Technology (AIST)/Tsukuba, 305-8568/Japon (4 aut.); Creative Advanced Technology Center/Scotts Valley, CA 95066/Etats-Unis (5 aut.)</AF><DT>Publication en série; Niveau analytique</DT><SO>IEEE transactions on audio, speech and language processing; ISSN 1558-7916; Etats-Unis; Da. 2008; Vol. 16; No. 2; Pp. 382-395; Bibl. 38 ref.</SO><LA>Anglais</LA><EA>Given a large audio database of music recordings, the goal of classical audio identification is to identify a particular audio recording by means of a short audio fragment. Even though recent identification algorithms show a significant degree of robustness towards noise, MP3 compression artifacts, and uniform temporal distortions, the notion of similarity is rather close to the identity. In this paper, we address a higher level retrieval problem, which we refer to as audio matching: given a short query audio clip, the goal is to automatically retrieve all excerpts from all recordings within the database that musically correspond to the query. In our matching scenario, opposed to classical audio identification, we allow semantically motivated variations as they typically occur in different Interpretations of a piece of music. To this end, this paper presents an efficient and robust audio matching procedure that works even in the presence of significant variations, such as nonlinear temporal, dynamical, and spectral deviations, where existing algorithms for audio identification would fail. Furthermore, the combination of various deformation- and fault-tolerance mechanisms allows us to employ standard indexing techniques to obtain an efficient, index-based matching procedure, thus providing an important step towards semantically searching large-scale real-world music collections.</EA><CC>001D04A04A2; 001D04A05D</CC><FD>Base de données audio; Document musical; Enregistrement son; Identification système; Immunité bruit; Traitement signal audio; Compression signal; Artefact; Similitude; Requête; Présentation de la ligne apellante; Base de données; Analyse sémantique; Algorithme; Tolérance faute; Indexation; Traitement signal acoustique; Présentation ligne appelante</FD><ED>Audio databases; Musical score; Sound recording; System identification; Noise immunity; Audio signal processing; Signal compression; Artefact; Similarity; Query; Calling line identification presentation; Database; Semantic analysis; Algorithm; Fault tolerance; Indexing; Acoustic signal processing; Calling line identification presentation</ED><SD>Documento musical; Registro sonido; Identificación sistema; Inmunidad ruido; Compresión señal; Artefacto; Similitud; Pregunta documental; Identificación de llamada entrante; Base dato; Análisis semántico; Algoritmo; Tolerancia falta; Indización</SD><LO>INIST-26266.354000183429570120</LO><ID>08-0185407</ID></server></inist></record>Pour manipuler ce document sous Unix (Dilib)
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