AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark
Saved in:
| Published in | Journal of the Franklin Institute Vol. 361; no. 1; pp. 418 - 428 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
01.01.2024
|
| Online Access | Get full text |
Cover
Loading…
| Author | Becker, Sören Vielhaben, Johanna Samek, Wojciech Lapuschkin, Sebastian Ackermann, Marcel Müller, Klaus-Robert |
|---|---|
| Author_xml | – sequence: 1 givenname: Sören surname: Becker fullname: Becker, Sören – sequence: 2 givenname: Johanna surname: Vielhaben fullname: Vielhaben, Johanna – sequence: 3 givenname: Marcel surname: Ackermann fullname: Ackermann, Marcel – sequence: 4 givenname: Klaus-Robert surname: Müller fullname: Müller, Klaus-Robert – sequence: 5 givenname: Sebastian orcidid: 0000-0002-0762-7258 surname: Lapuschkin fullname: Lapuschkin, Sebastian – sequence: 6 givenname: Wojciech orcidid: 0000-0002-6283-3265 surname: Samek fullname: Samek, Wojciech |
| BookMark | eNqFkMFOwzAMhnMYEtvgGcgLtCTN1rRIHKZpQKUBB8Y5ctNkpMuSKSkSe3syQBy4cLIt-7N-fRM0ct4phK4oySmh5XWf9zqA21nj8oIULKc0J6waoTFJ64wQVpyjSYx9GjklZIzaxXtn_ONT87K5wauPg_XBuO1XB8ZBaxVehMFoIw1Y3LhBWWu2ykmFtQ8YTjQGB_YYTcTeYcDR7A8Ja9PR2x7C7gKdabBRXf7UKXq9W22WD9n6-b5ZLtaZZKQcMqbmKVEN3YzTsqjmbK5r3nVpgILzutRQEQ6zVjFOqZRa1l1dUMk4q7hsu5pNEf_-K4OPMSgtDsGkAEdBiTjpEb341SNOegSlIulJ5O0fUpoBBuPdEMDYf_lP2rR11w |
| CitedBy_id | crossref_primary_10_1016_j_jisa_2024_103720 crossref_primary_10_1007_s00034_024_02656_8 crossref_primary_10_1007_s42979_025_03770_3 crossref_primary_10_1109_ACCESS_2024_3428336 crossref_primary_10_1016_j_patcog_2024_110309 crossref_primary_10_1007_s00521_024_10437_2 crossref_primary_10_1016_j_dib_2024_110678 crossref_primary_10_1016_j_inffus_2024_102923 crossref_primary_10_1038_s41928_024_01169_1 crossref_primary_10_1016_j_pnucene_2025_105722 |
| Cites_doi | 10.1038/ncomms13890 10.1145/3474121 10.1016/j.patcog.2016.11.008 10.6028/NIST.IR.4930 10.1109/ICASSP.2017.7952132 10.1038/s42256-023-00711-8 10.1016/j.tics.2022.07.003 10.1109/ICASSP.2017.7952190 10.1109/MSP.2012.2205597 10.1207/s15516709cog0000_76 10.1145/2783258.2788613 10.18653/v1/W17-5221 10.1109/JBHI.2020.3022989 10.1016/j.jneumeth.2016.10.008 10.1103/PhysRevD.101.094507 10.1038/s41467-019-08987-4 10.1146/annurev-pathmechdis-051222-113147 10.1109/JPROC.2021.3060483 10.1371/journal.pone.0130140 10.1109/TNNLS.2016.2599820 |
| ContentType | Journal Article |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.jfranklin.2023.11.038 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EndPage | 428 |
| ExternalDocumentID | 10_1016_j_jfranklin_2023_11_038 |
| GroupedDBID | --K --M -DZ -~X .~1 0R~ 1B1 1RT 1~. 1~5 29L 4.4 41~ 457 4G. 5GY 5VS 6TJ 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AAEDT AAEDW AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AATTM AAXKI AAXUO AAYFN AAYWO AAYXX ABAOU ABBOA ABDPE ABEFU ABFRF ABJNI ABMAC ABUCO ABWVN ABXDB ACCUC ACDAQ ACGFO ACGFS ACIWK ACNCT ACNNM ACRLP ACRPL ACZNC ADEZE ADGUI ADJOM ADMUD ADNMO ADTZH ADXHL AEBSH AECPX AEFWE AEIPS AEKER AETEA AFFNX AFJKZ AFTJW AFXIZ AGCQF AGHFR AGQPQ AGRNS AGUBO AGYEJ AHHHB AHJVU AHPAA AHZHX AIALX AIEXJ AIGVJ AIIUN AIKHN AITUG ALMA_UNASSIGNED_HOLDINGS AMRAJ ANKPU AOUOD APLSM APXCP ARUGR AXJTR BJAXD BKOJK BLXMC BNPGV CITATION CS3 D1Z EBS EFJIC EJD EO8 EO9 EP2 EP3 F5P FA8 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HAMUX HMJ HVGLF HZ~ H~9 IHE J1W JJJVA KOM LY7 M26 M41 MHUIS MO0 MVM N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SCC SDF SDG SES SET SEW SME SPC SPCBC SSB SSD SSH SST SSV SSW SSZ T5K TN5 UHS VOH WH7 WUQ XOL XPP ZCG ZMT ZY4 ~02 ~G- |
| ID | FETCH-LOGICAL-c306t-3e51009ad471628535f97dd716a27796fa807a4be3711ccfc9d921c37387cbd93 |
| ISSN | 0016-0032 |
| IngestDate | Thu Apr 24 23:02:17 EDT 2025 Tue Jul 01 03:53:23 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c306t-3e51009ad471628535f97dd716a27796fa807a4be3711ccfc9d921c37387cbd93 |
| ORCID | 0000-0002-6283-3265 0000-0002-0762-7258 |
| OpenAccessLink | https://doi.org/10.1016/j.jfranklin.2023.11.038 |
| PageCount | 11 |
| ParticipantIDs | crossref_primary_10_1016_j_jfranklin_2023_11_038 crossref_citationtrail_10_1016_j_jfranklin_2023_11_038 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2024-01-00 |
| PublicationDateYYYYMMDD | 2024-01-01 |
| PublicationDate_xml | – month: 01 year: 2024 text: 2024-01-00 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of the Franklin Institute |
| PublicationYear | 2024 |
| References | 10.1016/j.jfranklin.2023.11.038_b18 Lapuschkin (10.1016/j.jfranklin.2023.11.038_b29) 2019; 10 (10.1016/j.jfranklin.2023.11.038_b26) 2019; vol. 11700 Strodthoff (10.1016/j.jfranklin.2023.11.038_b11) 2018; 40 Thomas (10.1016/j.jfranklin.2023.11.038_b12) 2022; 26 Traunmüller (10.1016/j.jfranklin.2023.11.038_b44) 1995 Krizhevsky (10.1016/j.jfranklin.2023.11.038_b43) 2012 Anders (10.1016/j.jfranklin.2023.11.038_b33) 2021 Haunschmid (10.1016/j.jfranklin.2023.11.038_b36) 2020 LeCun (10.1016/j.jfranklin.2023.11.038_b24) 1998 Klauschen (10.1016/j.jfranklin.2023.11.038_b13) 2024; 19 10.1016/j.jfranklin.2023.11.038_b1 Powers (10.1016/j.jfranklin.2023.11.038_b48) 2011; 2 Alber (10.1016/j.jfranklin.2023.11.038_b32) 2018; 20 Wullenweber (10.1016/j.jfranklin.2023.11.038_b38) 2022 Achtibat (10.1016/j.jfranklin.2023.11.038_b41) 2023; 5 Hinton (10.1016/j.jfranklin.2023.11.038_b2) 2006; 30 Bach (10.1016/j.jfranklin.2023.11.038_b5) 2015; 10 Hinton (10.1016/j.jfranklin.2023.11.038_b17) 2012; 29 Samek (10.1016/j.jfranklin.2023.11.038_b8) 2021; 109 Parekh (10.1016/j.jfranklin.2023.11.038_b42) 2022 Ribeiro (10.1016/j.jfranklin.2023.11.038_b39) 2016 Rabiner (10.1016/j.jfranklin.2023.11.038_b19) 1993 Strodthoff (10.1016/j.jfranklin.2023.11.038_b27) 2021; 25 Kohlbrenner (10.1016/j.jfranklin.2023.11.038_b30) 2020 Hoffman (10.1016/j.jfranklin.2023.11.038_b46) 2018 Baehrens (10.1016/j.jfranklin.2023.11.038_b4) 2010; 11 Schütt (10.1016/j.jfranklin.2023.11.038_b14) 2017; 8 Jeyakumar (10.1016/j.jfranklin.2023.11.038_b34) 2020 Vielhaben (10.1016/j.jfranklin.2023.11.038_b40) 2023 10.1016/j.jfranklin.2023.11.038_b25 10.1016/j.jfranklin.2023.11.038_b9 Sturm (10.1016/j.jfranklin.2023.11.038_b10) 2016; 274 Becker (10.1016/j.jfranklin.2023.11.038_b47) 2018 10.1016/j.jfranklin.2023.11.038_b22 Slijepcevic (10.1016/j.jfranklin.2023.11.038_b28) 2022; 3 Fong (10.1016/j.jfranklin.2023.11.038_b6) 2017 Panayotov (10.1016/j.jfranklin.2023.11.038_b23) 2015 Lee (10.1016/j.jfranklin.2023.11.038_b16) 2009 Godfrey (10.1016/j.jfranklin.2023.11.038_b21) 1992 Lapuschkin (10.1016/j.jfranklin.2023.11.038_b31) 2016; 17 Schuller (10.1016/j.jfranklin.2023.11.038_b35) 2021 Anusuya (10.1016/j.jfranklin.2023.11.038_b20) 2009; 6 Melchiorre (10.1016/j.jfranklin.2023.11.038_b37) 2021 Montavon (10.1016/j.jfranklin.2023.11.038_b7) 2017; 65 Erhan (10.1016/j.jfranklin.2023.11.038_b3) 2009; 1341 Blücher (10.1016/j.jfranklin.2023.11.038_b15) 2020; 101 Samek (10.1016/j.jfranklin.2023.11.038_b45) 2017; 28 |
| References_xml | – start-page: 1097 year: 2012 ident: 10.1016/j.jfranklin.2023.11.038_b43 article-title: ImageNet classification with deep convolutional neural networks – volume: 11 start-page: 1803 issue: Jun year: 2010 ident: 10.1016/j.jfranklin.2023.11.038_b4 article-title: How to explain individual classification decisions publication-title: J. Mach. Learn. Res. – volume: 8 start-page: 13890 year: 2017 ident: 10.1016/j.jfranklin.2023.11.038_b14 article-title: Quantum-chemical insights from deep tensor neural networks publication-title: Nature Commun. doi: 10.1038/ncomms13890 – volume: 3 start-page: 1 issue: 2 year: 2022 ident: 10.1016/j.jfranklin.2023.11.038_b28 article-title: Explaining machine learning models for clinical gait analysis publication-title: ACM Trans. Comput. Healthc. doi: 10.1145/3474121 – start-page: 5206 year: 2015 ident: 10.1016/j.jfranklin.2023.11.038_b23 article-title: Librispeech: An ASR corpus based on public domain audio books – year: 2020 ident: 10.1016/j.jfranklin.2023.11.038_b34 article-title: How can I explain this to you? An empirical study of deep neural network explanation methods – volume: 65 start-page: 211 year: 2017 ident: 10.1016/j.jfranklin.2023.11.038_b7 article-title: Explaining NonLinear classification decisions with deep taylor decomposition publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.11.008 – volume: 20 start-page: 93:1 year: 2018 ident: 10.1016/j.jfranklin.2023.11.038_b32 article-title: Innvestigate neural networks! publication-title: J. Mach. Learn. Res. – start-page: 517 year: 1992 ident: 10.1016/j.jfranklin.2023.11.038_b21 article-title: Switchboard: Telephone speech corpus for research and development – year: 2020 ident: 10.1016/j.jfranklin.2023.11.038_b36 – volume: 1341 start-page: 1 issue: 3 year: 2009 ident: 10.1016/j.jfranklin.2023.11.038_b3 article-title: Visualizing higher-layer features of a deep network publication-title: Univ. Montreal – ident: 10.1016/j.jfranklin.2023.11.038_b22 doi: 10.6028/NIST.IR.4930 – ident: 10.1016/j.jfranklin.2023.11.038_b25 doi: 10.1109/ICASSP.2017.7952132 – year: 2018 ident: 10.1016/j.jfranklin.2023.11.038_b46 – start-page: 1135 year: 2016 ident: 10.1016/j.jfranklin.2023.11.038_b39 article-title: ”Why should I trust you?”: Explaining the predictions of any classifier – volume: 2 start-page: 37 issue: 1 year: 2011 ident: 10.1016/j.jfranklin.2023.11.038_b48 article-title: Evaluation: From precision, recall and F-measure to ROC, informedness, markedness & correlation publication-title: J. Mach. Learn. Technol. – volume: 5 start-page: 1006 issue: 9 year: 2023 ident: 10.1016/j.jfranklin.2023.11.038_b41 article-title: From attribution maps to human-understandable explanations through concept relevance propagation publication-title: Nat. Mach. Intell. doi: 10.1038/s42256-023-00711-8 – start-page: 1 year: 2020 ident: 10.1016/j.jfranklin.2023.11.038_b30 article-title: Towards best practice in explaining neural network decisions with LRP – start-page: 1342 year: 2022 ident: 10.1016/j.jfranklin.2023.11.038_b38 article-title: Coughlime: Sonified explanations for the predictions of COVID-19 cough classifiers – volume: 26 start-page: 972 issue: 11 year: 2022 ident: 10.1016/j.jfranklin.2023.11.038_b12 article-title: Interpreting mental state decoding with deep learning models publication-title: Trends in Cognitive Sciences doi: 10.1016/j.tics.2022.07.003 – ident: 10.1016/j.jfranklin.2023.11.038_b18 doi: 10.1109/ICASSP.2017.7952190 – volume: 17 start-page: 1 issue: 114 year: 2016 ident: 10.1016/j.jfranklin.2023.11.038_b31 article-title: The layer-wise relevance propagation toolbox for artificial neural networks publication-title: J. Mach. Learn. Res. – start-page: 1096 year: 2009 ident: 10.1016/j.jfranklin.2023.11.038_b16 article-title: Unsupervised feature learning for audio classification using convolutional deep belief networks – year: 2018 ident: 10.1016/j.jfranklin.2023.11.038_b47 – year: 2021 ident: 10.1016/j.jfranklin.2023.11.038_b33 – year: 2023 ident: 10.1016/j.jfranklin.2023.11.038_b40 article-title: Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees publication-title: Trans. Mach. Learn. Res. – year: 1993 ident: 10.1016/j.jfranklin.2023.11.038_b19 – volume: 29 start-page: 82 issue: 6 year: 2012 ident: 10.1016/j.jfranklin.2023.11.038_b17 article-title: Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2012.2205597 – volume: 30 start-page: 725 issue: 4 year: 2006 ident: 10.1016/j.jfranklin.2023.11.038_b2 article-title: Unsupervised discovery of nonlinear structure using contrastive backpropagation publication-title: Cogn. Sci. doi: 10.1207/s15516709cog0000_76 – ident: 10.1016/j.jfranklin.2023.11.038_b1 doi: 10.1145/2783258.2788613 – ident: 10.1016/j.jfranklin.2023.11.038_b9 doi: 10.18653/v1/W17-5221 – year: 1998 ident: 10.1016/j.jfranklin.2023.11.038_b24 – volume: 25 start-page: 1519 issue: 5 year: 2021 ident: 10.1016/j.jfranklin.2023.11.038_b27 article-title: Deep learning for ECG analysis: Benchmarks and insights from PTB-XL publication-title: IEEE J. Biomed. Health Inf. doi: 10.1109/JBHI.2020.3022989 – start-page: 531 year: 2021 ident: 10.1016/j.jfranklin.2023.11.038_b37 article-title: LEMONS: Listenable explanations for music recOmmeNder systems – start-page: 788 year: 2021 ident: 10.1016/j.jfranklin.2023.11.038_b35 article-title: Towards sonification in multimodal and user-FriendlyExplainable artificial intelligence – volume: vol. 11700 start-page: 1 year: 2019 ident: 10.1016/j.jfranklin.2023.11.038_b26 article-title: Explainable AI: Interpreting, explaining and visualizing deep learning – volume: 274 start-page: 141 year: 2016 ident: 10.1016/j.jfranklin.2023.11.038_b10 article-title: Interpretable deep neural networks for single-trial eeg classification publication-title: J. Neurosci. Methods doi: 10.1016/j.jneumeth.2016.10.008 – volume: 101 year: 2020 ident: 10.1016/j.jfranklin.2023.11.038_b15 article-title: Towards novel insights in lattice field theory with explainable machine learning publication-title: Phys. Rev. D doi: 10.1103/PhysRevD.101.094507 – volume: 40 year: 2018 ident: 10.1016/j.jfranklin.2023.11.038_b11 article-title: Detecting and interpreting myocardial infarction using fully convolutional neural networks publication-title: Physiol. Meas. – start-page: 35270 year: 2022 ident: 10.1016/j.jfranklin.2023.11.038_b42 article-title: Listen to interpret: Post-hoc interpretability for audio networks with NMF – volume: 10 start-page: 1096 issue: 1 year: 2019 ident: 10.1016/j.jfranklin.2023.11.038_b29 article-title: Unmasking clever hans predictors and assessing what machines really learn publication-title: Nature Commun. doi: 10.1038/s41467-019-08987-4 – volume: 6 start-page: 181 issue: 3 year: 2009 ident: 10.1016/j.jfranklin.2023.11.038_b20 article-title: Speech recognition by machine; a review publication-title: Int. J. Comput. Sci. Inf. Secur. – volume: 19 start-page: 541 issue: 1 year: 2024 ident: 10.1016/j.jfranklin.2023.11.038_b13 article-title: Toward explainable artificial intelligence for precision pathology publication-title: Annu. Rev. Pathol.: Mech. Dis. doi: 10.1146/annurev-pathmechdis-051222-113147 – volume: 109 start-page: 247 issue: 3 year: 2021 ident: 10.1016/j.jfranklin.2023.11.038_b8 article-title: Explaining deep neural networks and beyond: A review of methods and applications publication-title: Proc. IEEE doi: 10.1109/JPROC.2021.3060483 – year: 1995 ident: 10.1016/j.jfranklin.2023.11.038_b44 – start-page: 3449 year: 2017 ident: 10.1016/j.jfranklin.2023.11.038_b6 article-title: Interpretable explanations of black boxes by meaningful perturbation – volume: 10 issue: 7 year: 2015 ident: 10.1016/j.jfranklin.2023.11.038_b5 article-title: On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation publication-title: Plos One doi: 10.1371/journal.pone.0130140 – volume: 28 start-page: 2660 issue: 11 year: 2017 ident: 10.1016/j.jfranklin.2023.11.038_b45 article-title: Evaluating the visualization of what a deep neural network has learned publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2016.2599820 |
| SSID | ssj0017100 |
| Score | 2.5736365 |
| SourceID | crossref |
| SourceType | Enrichment Source Index Database |
| StartPage | 418 |
| Title | AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark |
| Volume | 361 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV09b9swECXcdGmHoukHmn4EHLoZFCSTlqxubtAiTeEscYpsAimSiI1ELhJ76dC_1L_YO1GkmDpAmiyCLJuEzHu4O5LvHgn5qDi4RviG5XpimVB2zGQhxgwii4GIoQrdVsjNjvPDU3F0Nj4bDP5ErKXNWiX1r1vrSh5iVXgGdsUq2XtYNnQKD-Ae7AtXsDBc_8vG041erGbH307mOLHv6XR456uiplctG8hpakTymy17EtsPZdAlaYZyeL1AveChgh-dX_pCnu3sFfNVf-B7zzgIk3vj2RonuBP_OY8qzn4scJNedUUhq3PZNCE0TLHZZXdu8wzLMHvaYtvRga9c_H4hN9fM8cLjlYuRiFYuOm-c5Qy8yg1vzPNsC3bOt4rOUbswLVxN-VYEcIsRy2RpuzFI8ID4BJVa-aQPen6j_59YGBiKnvy2rEJHFXYEM6YKOnpEHo9gXoKONfkdOEUZSiW50O_-2A1C4a1vFKVDUV4zf06edSalU4euXTIwzQvyNJKpfElUj7NPNKCMRiijPcpojDIKKKMtyqhHGV01VFKHMhpQ9oqcfv0yPzhk3dkcrIZJ5ppxA848LaUWKEEGOd_YloXW8EHCwJS5lZO0kEIZXmTgC2xd6nKU1aijVdRKl_w12WlWjXlD6IhbDkl1PUmtEEpAhlqmqRGZNSrVPNd7JPdDVNWdcD2en3JR3WGkPZKGhj-ddstdTd7ev8k78qQH93uys77amA-QqK7VfguOvxOmlgc |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=AudioMNIST%3A+Exploring+Explainable+Artificial+Intelligence+for+audio+analysis+on+a+simple+benchmark&rft.jtitle=Journal+of+the+Franklin+Institute&rft.au=Becker%2C+S%C3%B6ren&rft.au=Vielhaben%2C+Johanna&rft.au=Ackermann%2C+Marcel&rft.au=M%C3%BCller%2C+Klaus-Robert&rft.date=2024-01-01&rft.issn=0016-0032&rft.volume=361&rft.issue=1&rft.spage=418&rft.epage=428&rft_id=info:doi/10.1016%2Fj.jfranklin.2023.11.038&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_jfranklin_2023_11_038 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0016-0032&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0016-0032&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0016-0032&client=summon |