{ "$schema": "/api/schemas/documents.schema.json", "apiVersion": "1.1.0", "lastModified": "2026-10-07T20:50:36.680Z", "sourcePath": "src/main/data/docs", "docId": "10.5594-JMI.2022.3160793", "document": { "abbrevTitle": "SMPTE Mot. Imag. J", "abbrevTitle$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "abstract": "Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) is the first standards organization to develop data coding standards that have artificial intelligence (AI) as their core technology. MPAI believes that universally accessible standards for AI-based data coding can have the same positive effects on AI as standards had on digital media. Elementary components of MPAI standards–AI modules (AIMs)–expose standard interfaces for operation in a standard AI framework (AIF). As their performance may depend on the technologies used, MPAI expects that competing developers providing AIMs will promote horizontal markets of AI solutions that build on and further promote AI innovation. Finally, the MPAI framework licences (FWLs) provide guidelines to intellectual property right (IPR) holders facilitating the availability of compatible licenses to standard users.", "abstract$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "authors": [ { "bio": "Andrea Basso received a PhD degree, and is an advisor at the Progress Tech Transfer fund, a chief technology officer at MITO Technology, Milan, Italy, a senior expert World Intellectual Property Organization/European Commission, and a director at Synesthesia, Turin, Italy. While at Bell and AT&T Labs, Murray Hill, NJ, he contributed to the Internet Engineering Task Force (IETF) and the International Organization for Standardization/Motion Picture Experts Group (ISO/MPEG), and the International Multimedia Telecommunications Consortium (IMTC). He has authored or coauthored over 60 articles and holds 174 patents.", "name": "Andrea Basso" }, { "bio": "Paolo Ribeca is a physicist by education but for 15 years he has specialized in the analysis of high- throughput sequencing data, being particularly interested in the development of algorithms and workflows for alignment, de novo assembly, and compression. He is delighted whenever he can apply those techniques and answer complex biological questions.", "name": "Paolo Ribeca", "orcid": "0000-0001-5599-3933" }, { "bio": "Marina Bosi, a pioneer in the development of digital audio coding, is a founding director of the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Organization, Geneva, Switzerland, and the chair of MPAI-Context-Based Audio Enhancement (MPAI-CAE). A fellow and past president of the Audio Engineering Society, Bosi was chief technology officer of MPEG LA, LLC, Denver, CO, vice president-technology at DTS, Inc., Los Angeles, CA, and was a member of the research team that created Dolby Digital at Dolby Laboratories, San Francisco, CA, where she also led the MPEG-2 AAC development.", "name": "Marina Bosi" }, { "bio": "Niccolò Pretto is a senior postdoctoral research fellow with the Department of Information Engineering, University of Padova, Padua, Italy. His research is primarily focused on sound and music computing, applying computer science to the preservation and access to historical audio documents and cultural heritage.", "name": "Niccolò Pretto", "orcid": "0000-0002-3742-7150" }, { "bio": "Gérard Chollet studied linguistics, electrical engineering, and computer science at the University of California at Santa Barbara, Santa Barbara, CA, where he was granted a PhD in computer science and linguistics. In 1983, he joined a newly created Centre national de la recherche scientifique (CNRS) Research Unit at ENST (now Institut Polytechnique de Paris), Palaiseau, France. He supervised more than 40 doctoral theses. CNRS granted him an emeritus status in 2012. He is currently consulting for Intelligent Voice Ltd., London, U.K., Speech Morphing Inc., San Jose, CA, and Zaion.ai, Paris, France. His main publications are available at http://scholar.google.co.uk/citations?user=NakTCiYAAAAJ&hl=en", "name": "Gérard Chollet" }, { "bio": "Michelangelo Guarise is a founder of Volumio, Florence, Italy, the market leader of hi-fi music playback ecosystem. He has been involved in physical computing and user experience research, now focusing on AI and machine learning (ML) on the field applications for high-performance and adaptive music playback systems.", "name": "Michelangelo Guarise" }, { "bio": "Miran Choi is a principal researcher at the Electronics and Telecommunication Research Institute (ETRI), Daejeon, South Korea. Her research topics are natural language processing and human computer interaction (HCI). She is participating in standardization activities in ITU-T, International Organization for Standardization (ISO), and MPAI, where she develops standards on language-related technology and user interface.", "name": "Miran Choi" }, { "bio": "Leonardo Chiariglione received a MS from the Polytechnic of Turin, Turin, Italy, and a PhD from the University of Tokyo, Tokyo, Japan. He founded and chaired the Moving Picture Experts Group (MPEG) for 32 years, and proposed and chairs the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI), for AI-enabled data coding standards.", "name": "Leonardo Chiariglione" }, { "bio": "Roberto Iacoviello is a lead research engineer. He graduated from the Politecnico di Torino, Turin, Italy. Since 2007, he has been working at Rai Research and Development, Turin. His current research focuses on artificial intelligence applied to video compression, and augmented reality in broadcast television. He leads the Video Evaluation Group at the European Broadcasting Union (EBU) and actively participates in MPEG and MPAI meetings.", "name": "Roberto Iacoviello", "orcid": "0000-0002-5336-1462" }, { "bio": "Franesco Banterle is a researcher with the Visual Computing Laboratory at Consiglio Nazionale delle Richerch- (CNR)-Institute of Information Science and Technologies (ISTI), Pisa, Italy. He received a PhD in engineering from the University of Warwick, Coventry, U.K., in 2009. He developed Inverse Tone Mapping, which bridges classic imaging and high-dynamic range (HDR) imaging. His main research fields are HDR imaging and deep learning.", "name": "Franesco Banterle", "orcid": "0000-0002-6374-6657" }, { "bio": "Alessandro Artusi received a PhD in computer science from the Vienna University of Technology, Vienna, Austria, in 2004. He is the team leader of the DeepCamera Group at CYENS Nicosia, Cyprus. His research interests include image/video processing, computer graphics, computer vision, and color science, with a particular focus to deploy the next generation of imaging/video pipeline.", "name": "Alessandro Artusi", "orcid": "0000-0002-4502-663X" }, { "bio": "Francesco Gissi received an MSc in computer engineering. He is currently pursuing a PhD in information technology for engineering with the University of Sannio, Benevento, Italy. He is currently working as a data architectures, AI and advanced analytics engineer at Kebula, Naples, Italy. His principal research interests are application of AI models and approaches on video analytics tasks, audio-video compression pipelines via content-based analysis with deep learning techniques, and advanced learning algorithms.", "name": "Francesco Gissi", "orcid": "0000-0003-0335-849X" }, { "bio": "Attilio Fiandrotti received a PhD in computer science from the Politecnico di Torino, Turin, Italy, in 2010. He is currently an assistant professor at the Dipartimento di Informatica, Università di Torino, Turin, and holds a position as maıtre de confèrènces with the Multimedia Group, LTCI, Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France. His current research interests focus mainly on deep learning techniques for image and video analysis, compression, and synthesis and the distribution of multimedia contents over wireless packet networks.", "name": "Attilio Fiandrotti" }, { "bio": "Giovanni Ballocca received a master’s in physics from the Università di Torino, Turin, Italy. He is a project manager with Sisvel Technology, None Torinese, IT, focusing on research and development projects on compression and distribution of multimedia content. He is also an expert in the field of intellectual property right (IPR) management and licensing in the consumer electronics field.", "name": "Giovanni Ballocca", "orcid": "0000-0002-0252-1753" }, { "bio": "Marco Mazzaglia is a video game evangelist for Synesthesia, Italy. Since 2008, he has worked on more than 30 original titles and conversions on last-generation game consoles and for the B2B world. He is an adjunct professor of game design and gamification for the Polytechnic of Turin, Turin, Italy, at the master’s degree courses for cinema and media engineering and computer engineering.", "name": "Marco Mazzaglia" }, { "bio": "Scott Moskowitz graduated cum laude from the Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania. He holds more than 110 patents in digital watermarks, product license keys, address space layout randomization (ASLR), and so on. He presented his acclaimed “Cuba” photograph series at Leica Store Miami. He is a senior member of Institute of Electrical and Electronics Engineers (IEEE), Assoication for Computing Machinery (ACM), and Society of Photographic Instrumentation Engineers (SPIE). He is fluent in Japanese.", "name": "Scott Moskowitz", "orcid": "0000-0002-2103-1370" } ], "authors$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "contentType": "orig-research", "contentType$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "copyright": { "holder": "SMPTE", "holder$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "year": "2022", "year$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" } }, "copyright$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "docId": "10.5594-JMI.2022.3160793", "docId$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "docLabel": "SMPTE Motion Imaging Journal ( Volume: 131, Issue: 4, May 2022)", "docLabel$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "docTitle": "AI-Based Media Coding Standards", "docTitle$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "docType": "Journal Article", "docType$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "doi": "10.5594/JMI.2022.3160793", "doi$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article 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"smpte-idams-publication@v1" }, "keywords": [ "Artificial Intelligence", "Audio Enhancement", "IP License", "Standards", "Video Compression" ], "keywords$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "number": "4", "number$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "pages": "10–20", "pages$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "publicationDate": "2022-05-01", "publicationDate$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "publisher": "SMPTE", "publisher$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "publisherLocation": { "city": "White Plains, NY", "city$meta": { "confidence": "high", "note": "Ingested from SMPTE IDAMS (_source/SMPTE/Journal Article Repository/2022/7261654/9772088/09772095.xml) via idamsIngest.js", "source": "parsed", "updated": "2026-10-07T17:09:33.718Z", "version": "smpte-idams-publication@v1" }, "country": "USA", "country$meta": { "confidence": "high", 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