Moving Picture, Audio and Data Coding
by Artificial Intelligence

Archives: 2022-05-28

More members for the MPAI Standards Family

The latest – 15 June 2024 – MPAI General Assembly (MPAI-44) proved, if ever there was a need, that MPAI produces non only standards, but also promising new projects. MPAI-44 launched three new projects on 6 degrees of freedom audio (CSAE-6DF), technologies for connected autonomous vehicle components, and technologies for the MPAI Metaverse Model.

The CAE-6DF Call is seeking innovative technologies that enable users to walk in a virtual space representing a remote real space and enjoy the same experience as if they were in the remote space. Visit the CAE-6DF page and register to attend the online presentation of the Call of the 28th of May, communicate your intention to respond to the Call by the 4th of June, and submit your response by the 16th of September.

The CAV-TEC Call requests technologies that build on the Reference Architecture of the Connected Autonomous Vehicle (CAV-ARC) to achieve a componentisation of connected autonomous vehicles. Visit the CAV-TEC page and register to attend the online presentation of the Call of the 6th of July, communicate your intention to respond to the Call by the 14th of June, and submit your response by the 5th of July.

The MMM-TEC Call requests technologies that build on the Reference Architecture of the MPAI Metaverse Model (MMM-ARC) and enable a metaverse instance to interoperate with other metaverse instances. Visit the MMM-TEC page and register to attend the online presentation of the Call of the 31st of July, communicate your intention to respond to the Call by the 7th of June, and submit your response by the 6th of July.

MPAI-44 has brought more results.

Four existing standards have been republished with significant new material that extends the current functionalities of the four and supports the needs of the three new projects in the form of extensions of existing standards that are published for Community Comments:

  • Object and Scene Description (MPAI-OSD) V1.1 adds a new Use Case for automatic audio-visual analysis of television programs and new functionalities for Visual and Audio-Visual Objects and Scenes.
  • The Cases of Context-based Audio Experience (MPAI-CAE) V2.2 standard (CAE-USC) supports new functionalities for Audio Object and Scene Descriptors.
  • The Multimodal Conversation (MPAI-MMC) V2.2 standard introduces new AI Modules and new Data Formats to support the new MPAI-OSD Television Media Analysis Use Case.
  • The Portable Avatar Format (MPAI-PAF) V1.2 standard extends the specification of the Portable Avatar to support new functionality requested by the CAV-TEC and MMM-TEC Calls.

Everybody is welcome to review the draft standards (new versions of existing standards) and send comments to the MPAI Secretariat by 23:59 UTC of the relevant day.  Comments will be considered when the standards will be published in final form.

The standards mentioned above cover a significant share of the MPAI portfolio, but your navigation need not stop here. If you wish to delve into the other MPAI standards, you can go to their appropriate web pages where you can read overviews and find many links to relevant web pages. Each MPAI page contains a web version and other support material such as PowerPoint presentations and video recordings.


MPAI publishes a record three Calls for Technologies, four new Standards for Community Comments and one Reference Software Specification

Geneva, Switzerland – 15 May 2024. MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence – the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 44th General Assembly (MPAI-44) with an unprecedented display of productivity.

Three Calls for Technologies:

  • Context-based Audio Enhancement (MPAI-CAE): Six Degrees of Freedom (CAE-6DF) to develop an ambitious standard that will enable users to have the spatial experience of a remote audio environment by “walking into it”. Register for the online presentation on 2024/05/28 16:00 UTC.
  • Connected Autonomous Vehicle (MPAI-CAV) – Technologies to extend the existing MPAI-CAV – Architecture standard by supporting reference to specific technologies that are the target of the Call. Register for the online presentation on 2024/06/06 16:00 UTC.
  • MPAI Metaverse Model (MPAI-MMM) – Technologies to extend the existing MPAI-MMM – Architecture standard by supporting reference to specific technologies that are the target of the Call. Register for the online presentation on 2024/05/31 16:00 UTC.

Four new Standards published with a request for Community Comments:

  • Object and Scene Description (MPAI-OSD) V1.1 includes a new Use Case for automatic audio-visual analysis of television programs and new functionalities for Visual and Audio-Visual Objects and Scenes.
  • Context-based Audio Experience (MPAI-CAE) Use Cases (CAE-USC) V2.2 supports new functionalities in Audio Object and Audio Scene Descriptors.
  • Multimodal Conversation (MPAI-MMC) V2.2 introduces new AI Modules and new Data Formats to support the new MPAI-OSD Television Media Analysis Use Case.
  • Portable Avatar Format (MPAI-PAF) V1.2 extends the specification of the Portable Avatar to support new functionality requested by the MPAI-CAV and MPAI-MMM Calls.

One Reference Software Specification:

MPAI’s scope of activities is quite wide as shown by its 11 already published standards that include 18 Use Cases and some 75 AI Modules, and 65 Data Types shared across different standards. MPAI has succeeded in developing a common layer of technologies supporting a variety of application domains.

MPAI is continuing its work plan that involves the following activities:

  1. AI Framework (MPAI-AIF): developing open-source applications based on the AI Framework.
  2. AI for Health (MPAI-AIH): developing the specification of a system enabling clients to improve models processing health data and federated learning to share the training.
  3. Context-based Audio Enhancement (CAE-DC): preparing new projects.
  4. Connected Autonomous Vehicle (MPAI-CAV): Functional Requirements of the data used by the MPIA-CAV – Architecture standard.
  5. Compression and Understanding of Industrial Data (MPAI-CUI): preparation for an extension to existing standard that includes support for more corporate risks.
  6. End-to-End Video Coding (MPAI-EEV): video coding using AI-based End-to-End Video coding.
  7. AI-Enhanced Video Coding (MPAI-EVC). video coding with AI tools added to existing tools.
  8. Human and Machine Communication (MPAI-HMC): developing reference software.
  9. Multimodal Conversation (MPAI-MMC): developing reference software and conformance testing and exploring new areas.
  10. MPAI Metaverse Model (MPAI-MMM): developing reference software specification and identifying metaverse technologies requiring standards.
  11. Neural Network Watermarking (MPAI-NNW): developing reference software for enhanced applications.
  12. Portable Avatar Format (MPAI-PAF): developing reference software, conformance testing and new areas for digital humans.
  13. AI Module Profiles (MPAI-PRF): to specify which features an AI Module supports.
  14. Server-based Predictive Multiplayer Gaming (MPAI-SPG): developing technical report on mitigation of data loss and cheating.
  15. XR Venues (MPAI-XRV): developing the standard enabling improved development and execution of Live Theatrical Performance.

Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members.

Please visit the MPAI website, contact the MPAI secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.


A new brick for the MPAI architecture

At its 43rd General Assembly of 2024 April17, MPAI approved the publication of the draft AI Module Profiles (MPAI-PRF) standard with a request for Community Comments. The scope of MPAI-PRF is to provide a solution to the problem that MPAI finds more and more often: the AI Modules (AIM) it specifies in different standards have the same basic functionality but may have different features.

First two words about AIMs. MPAI develops application-oriented standards for applications that MPAI calls AI Workflows (AIW) that can be broken down into components called Ai Modules. AIWs are specified by what they do (functions), by the input and output data and by how its AIMs are interconnected (Topology). Similarly, AIMs are specified by what they do (functions) and by the input and output data. AIMs are Composite if they include interconnected AIMs or Basic if its internal structure is unknown.

Let’s look at the Natural Language Understanding (MMC-NLU) AIM of Figure 1.

Figure 1 – The Natural Language Understanding (MMC-NLU) AIM

The NLU AIM’s basic function is to receive a Text Object – directly from a keyboard or through an Automatic Speech Recognition (ASR) AIM (in which case it is called Recognised Text) and produce a Text Object that can be Refined Text in case it is the output of an ASR AIM and the Meaning of the text. The NLU AIM, however, can also receive “spatial information” about the Audio and/or Visual Objects in terms of their position and orientation in the Scene that the machine is processing. Obviously, this additional information helps the machine produce a response that is more attuned to the context.

This a case shows that there is a need to unambiguously name these two functionally equivalent but very different instances of the same NLU AIMs.

The notion of Profiles, originally developed by MPEG in the summer of 1992 for the MPEG-2 standard and then universally adopted in the media domain comes in handy. An AIM Profile is a label that uniquely identifies the set of AIM Attributes of an AIM instance where Attribute is “input data, output data, or functionality that uniquely characterises an AIM instance”. In the case of the NLU AIM, Text Object (TXO), Recognised Text (TXR), Object Instance Identifier (OII), Audio-Visual Scene Geometry (AVG), and Meaning (TXD or Text Descriptors).

The Draft AI Module Profiles (MPAI-PRF) Standard offers two ways to signal the Attributes of an AIM: those that are supported or those that are not supported. Both can be used, but likely the first (list of those that are supported) if it is shorter than the second (list of those that are not supported) and vice versa. The Profile of an NLU AIM instance that does not handle spatial information can thus be labelled in two ways:

List of supported Attributes MMC-NLU-V2.1(ALL-AVG-OII)
List of unsupported Attributes MMC-NLU-V2.1(NUL+TXO+TXR)

V2.1 refers to the version of the Multimodal Conversation MPAI-MMC standards that specifies the NLU AIM. ALL signals that the Profile is expressed in “negative logic” in the sense that the removed Attributes are AVG for Audio-Visual Scene Geometry and OII. NUL signals that the Profile is expressed in “positive logic” in the sense that the added Attributes are TXO for Text Object from a keyboard and TXR for Recognised Text.

The Profile story does not end here. Attributes are not always sufficient to identify the capabilities of an AIM instance. Let’s take the Entity Dialogue Processing (MMC-EDP) of Figure 2 an AIM that uses different information sources derived from the information issued by an Entity, typically a human – but potentially also a machine – with which this machine is communicating.

Figure 2 – The  Entity Dialogue Processing (MPAI-EDP)

The input data is Text Object and Meaning (output of the NLU), Audio or Visual Instance ID and Scene Geometry (already used by the NLU AIM) and Personal Status, a data type that represents the internal state of the Entity in terms of three Factors (Cognitive State, Emotion, and Social Attitude) and four Modalities (Text, Speech, Face, and Body) for each Factor.

The output of the EDP AIM is Text that can be fed to a regular Text-To-Speech AIM, but can additionally be the machine’s Personal Status, obviously pretended by the machine, but of great value for the Personal Status Display (PAF-PSD) AIM depicted in Figure 3.

Figure 3 – The Personal Status Display AIM

This uses the machine’s Text and Personal Status (IPS) to synthesise the machine using an Avatar Model (AVM) as a speaking avatar. An AIM instance of the PSD AIM may support the Personal Status, but only its Speech (PS-Speech, PSS) and Face (PS-Face, PSF) Factors, as in the case of a PSD AIM designed for sign language. This is formally represented by the following two expressions:

List of supported Attributes PAF-PSD-V1.1(ALL@IPS#PSS#PSF)
List of unsupported Attributes PAF-PSD-V1.1(NUL+TXO+AVM@IPS#PSF#PSG

@IPS#PSS#PSF in the first expression indicates that the PSD AIM supports all Attributes, but the Personal Status only includes the Speech and Face Factors. In the second expression +TXO+AVM indicates that the PSD AIM supports Text and Avatar Model and @IPS#PSF#PSG that the Personal Status Factors supported are Face (PSF) and Gesture (PSG).

AI Module Profiles is another element of the AI application infrastructure that MPAI is building with its standards. Read the AI Module Profiles standard for an in-depth understanding. Anybody can submit comments to the draft by sending an email to the MPAI secretariat by 2024/05/08T23:59. MPAI will consider each comment received for possible inclusion in the final version of MPAI-PRF.


MPAI publishes the draft AI Module Profile Standard with a request for Community Comments

Geneva, Switzerland – 17 April 2024. MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence – the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 43rd General Assembly (MPAI-43) approving the publication of the draft AI Module Profile V1.0 Standard with a request for Community Comments.

AI Module Profiles (MPAI-PRF) V1.0 enables the signalling of AI Module Attributes – input data, output data, or functionality – that uniquely characterise an AIM instance. An AIM Profile is thus a label that uniquely identifies the set of AIM Attributes that are either supported or not supported by that AIM instance. Anybody can submit comments to the draft by sending an email to the MPAI secretariat by 2024/05/08T23:59.

MPAI also informs that the code, the presentation file, and the video recording of the V1.1 version of the Neural Network Watermarking (MPAI-NNW) Reference Software Specification presented  of the on the 16th of April are now publicly available. The software enables a user to make queries that include a text and an image and obtain a watermarked vocal response that enables the issuer of the query to ascertain that the response is from the intended source. The second software can be used to run watermarked AI-based applications on resource-constrained processing platforms without significant performance loss.

MPAI is continuing its work plan that involving the following activities:

  1. AI Framework (MPAI-AIF): developing open-source applications based on the AI Framework.
  2. AI for Health (MPAI-AIH): developing the specification of a system enabling clients to improve models processing health data and federated learning to share the training.
  3. Context-based Audio Enhancement (CAE-DC): preparing new projects.
  4. Connected Autonomous Vehicle (MPAI-CAV): Functional Requirements of the data used by the MPIA-CAV – Architecture standard.
  5. Compression and Understanding of Industrial Data (MPAI-CUI): preparation for an extension to existing standard that includes support for more corporate risks.
  6. End-to-End Video Coding (MPAI-EEV): video coding using AI-based End-to-End Video coding.
  7. AI-Enhanced Video Coding (MPAI-EVC). video coding with AI tools added to existing tools.
  8. Human and Machine Communication (MPAI-HMC): developing reference software.
  9. Multimodal Conversation (MPAI-MMC): developing reference software and conformance testing and exploring new areas.
  10. MPAI Metaverse Model (MPAI-MMM): developing reference software specification and identifying metaverse technologies requiring standards.
  11. Neural Network Watermarking (MPAI-NNW): reference software for enhanced applications.
  12. Portable Avatar Format (MPAI-PAF): reference software, conformance testing and new areas.
  13. Server-based Predictive Multiplayer Gaming (MPAI-SPG): technical report on mitigation of data loss and cheating.
  14. XR Venues (MPAI-XRV): development of the standard.

Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members.

Please visit the MPAI website, contact the MPAI secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.

 


MPAI releases reference software leveraging AI Framework and Neural Network Watermarking for Generative AI applications

Geneva, Switzerland – 20 March 2024. MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence – the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 42nd General Assembly (MPAI-42) approving the release of Reference Software using Neural Network Watermarking for Generative AI applications.

The new V1.1 version of the Neural Network Watermarking (MPAI-NNW) Reference Software includes an implementation of the AIF Framework and of an AI Workflow enabling a user to make queries that include a text and an image and obtain a vocal response. This inference is watermarked, to enable the issuer of the query to ascertain that the response they receive is from the intended source. The Software will be presented online on the 16th of April at 15 UTC. Register at https://us06web.zoom.us/meeting/register/tZ0udeutqT0vHdBh1DLiUxoRr59cUs7iQzzN.

Presentations and video recordings of all MPAI standards are available (ppt= PowerPoint file), YT=YouTube, nYT=WimTV):

AI Framework (MPAI-AIF) ppt YT nYT
Context-based Audio Enhancement (MPAI-CAE) ppt YT nYT
Connected Autonomous Vehicle (MPAI-CAV) – Architecture ppt  YT nYT
Compression and Understanding of Industrial Data (MPAI-CUI) ppt YT nYT
Governance of the MPAI Ecosystem (MPAI-GME) ppt YT nYT
Human and Machine Communication (MPAI-HMC) ppt YT nYT 
Multimodal Conversation (MPAI-MMC) ppt YT nYT
MPAI Metaverse Model (MPAI-MMM) – Architecture ppt  YT  nYT
Neural Network Watermarking MPAI-NNW) ppt YT nYT
Object and Scene Description (MPAI-OSD) ppt YT nYT
Portable Avatar Format (MPAI-PAF) ppt  YT  nYT

MPAI is continuing its work plan that involving the following activities:

  1. AI Framework (MPAI-AIF): developing open-source applications based on the AI Framework.
  2. AI for Health (MPAI-AIH): developing the specification of a system enabling clients to improve models processing health data and federated learning to share the training.
  3. Context-based Audio Enhancement (CAE-DC): preparing new projects.
  4. Connected Autonomous Vehicle (MPAI-CAV): Functional Requirements of the data used by the MPIA-CAV – Architecture standard.
  5. Compression and Understanding of Industrial Data (MPAI-CUI): preparation for an extension to existing standard that includes support for more corporate risks.
  6. End-to-End Video Coding (MPAI-EEV): video coding using AI-based End-to-End Video coding.
  7. AI-Enhanced Video Coding (MPAI-EVC). video coding with AI tools added to existing tools.
  8. Human and Machine Communication (MPAI-HMC): developing reference software.
  9. Multimodal Conversation (MPAI-MMC): developing reference software and conformance testing and exploring new areas.
  10. MPAI Metaverse Model (MPAI-MMM): developing reference software specification and identifying metaverse technologies requiring standards.
  11. Neural Network Watermarking (MPAI-NNW): reference software for enhanced applications.
  12. Portable Avatar Format (MPAI-PAF): reference software, conformance testing and new areas.
  13. Server-based Predictive Multiplayer Gaming (MPAI-SPG): technical report on mitigation of data loss and cheating.
  14. XR Venues (MPAI-XRV): development of the standard.

Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members.

Please visit the MPAI website, contact the MPAI secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.

 

 


Recent MPAI standards – presentations and video recordings

In the last few months, MPAI has published eight new or update MPAI standards. They have been presented online in the 11-15 March 2024 week.

Here are the titles of the standards with links to the presentations and video recording provided by two services. They are a good opportunity to stay abreast of the progress in MPAI

rev MPAI Metaverse Model  (MPAI-MMM) – Architecture ppt  YT  nYT
new Portable Avatar Format  (MPAI-PAF) ppt  YT  nYT
new Human and Machine Communication  (MPAI-HMC) ppt YT nYT 
new Connected Autonomous Vehicle  (MPAI-CAV) – Architecture ppt  YT nYT
rev Context-based Audio Enhancement (MPAI-CAE) ppt YT nYT
new Object and Scene Description (MPAI-OSD) ppt YT nYT
rev Multimodal Conversation  (MPAI-MMC) ppt YT nYT
rev AI Framework (MPAI-AIF) ppt YT nYT
MPAI presentation ppt YT nYT

MPAI publishes two standards: the new version of Context-based Audio Enhancement and the new Human and Machine Communication

Geneva, Switzerland – 21 February 2024. MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence – the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 41st General Assembly (MPAI-41) approving the publication of two standards and announcing the availability of all its standards in linked form on the web.

Context-based Audio Enhancement (MPAI-CAE) V2.1 extends the previously published Version 2.0 adding full online references to the specification of all AI Workflows, AI Modules, JSON Metadata, and Data Types used by the standard.

Human and Machine Communication (MPAI-HMC) V1.0 integrates a wide range of technologies from existing MPAI standards to enable new forms of communication between entities, i.e., humans present or represented in a real or virtual space or machines represented in a virtual space as speaking avatars and acting in a context using text, speech, face, gesture, and audio-visual scene in which they are embedded. It.

In the 11-15 March week, MPAI will be presenting its recently published standards at a series of planned 40-min online sessions. The presentations will illustrate the scope, the features, and the technologies of each standard and will be followed by open discussions. The new web-based access to all published MPAI standards will also be presented. All times are UTC

Standard March Registr.
AI Framework (MPAI-AIF) 11 T16:00 Link
Context-based Audio Enhancement (MPAI-CAE) 12 T17:00 Link
Connected Autonomous Vehicle (MPAI-CAV) – Architecture 13 T15:00 Link
Human and Machine Communication (MPAI-HMC) 13 T16:00 Link
Multimodal Conversation (MPAI-MMC) 12 T14:00 Link
MPAI Metaverse Model (MPAI-MMM) – Architecture 15 T15:00 Link
Portable Avatar Format (MPAI-PAF) 14 T14:00 Link

MPAI is continuing its work plan that involving the following activities:

  1. AI Framework (MPAI-AIF): developing open-source applications based on the AI Framework.
  2. AI for Health (MPAI-AIH): developing the specification of a system enabling clients to improve models processing health data and federated learning to share the training.
  3. Context-based Audio Enhancement (CAE-DC): preparing new projects.
  4. Connected Autonomous Vehicle (MPAI-CAV): Functional Requirements of the data used by the MPIA-CAV – Architecture standard.
  5. Compression and Understanding of Industrial Data (MPAI-CUI): preparation for an extension to existing standard that includes support for more corporate risks.
  6. Human and Machine Communication (MPAI-HMC): developing reference software.
  7. Multimodal Conversation (MPAI-MMC): developing reference software and conformance testing, and exploring new areas.
  8. MPAI Metaverse Model (MPAI-MMM): developing reference software specification and identifying metaverse technologies requiring standards.
  9. Neural Network Watermarking (MPAI-NNW): reference software for enhanced applications.
  10. Portable Avatar Format (MPAI-PAF): reference software, conformance testing and new areas.
  11. End-to-End Video Coding (MPAI-EEV): video coding using AI-based End-to-End Video coding.
  12. AI-Enhanced Video Coding (MPAI-EVC). video coding with AI tools added to existing tools.
  13. Server-based Predictive Multiplayer Gaming (MPAI-SPG): technical report on mitigation of data loss and cheating.
  14. XR Venues (MPAI-XRV): development of the standard.

Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members.

Please visit the MPAI website, contact the MPAI secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.

 

 


Standards that innovate technology and standardisation

At its 40th General Assembly (MPAI-40), MPAI approved one draft, one new, and three extension standards. For an organisation that has already nine standards in its game bag, this may not look like big news. There are two reasons, though, to consider this a remarkable moment in the MPAI short but intense life.

The first reason is that the draft standard posted for Community Comments – Human and Machine Communication (MPAI-HMC) – does not specify new technologies but leverages technologies from existing MPAI standards: Context-based Audio Enhancement (MPAI-CAE), Multimodal Conversation (MPAI-MMC), the newly approved Object and Scene Description (MPAI-OSD), and Portable Avatar Format (MPAI-PAF).

If not new technologies, what does MPAI-HMC specify then? To answer this question let’s consider Figure 1.

Figure 1 – The MPAI-HMC communications model

The human labelled as #1 is part of a scene with audio and visual attributes and communicates with the Machine by transmitting speech information and the entire audio-visual scene including him or herself. The Machine receives that information, processes it, and emits internally generated audio-visual scenes that include itself uttering vocal and displaying visual manifestations of its own internal state generated to interact more naturally with the human. The human may also communicate with the Machine when other humans are in the scene with him or her and the Machine can discern the individual human and identify (i.e., give a name to) audio and visual objects. However, only one human at a time can communicate with the Machine.

The Machine need not capture the human in a real space. His or her digital representation can be rendered in a Virtual Space as a Digitised Human. The human may not be alone but together with other Digitised Humans or with Virtual Humans, i.e., audio-visual representations of processes, such as Machines. For this reason, we will use the word Entity to indicate both a human or their avatar and a Machine rendered as an avatar.

The Machine can also act as an interpreter between the Entities and Contexts labelled as #1 or #2 and #3 or #4. By Context we mean information surrounding an Entity that provides additional insight into the information communicated by the Entity. An example of Context is language and, more generally, culture.

Communication between #1 and #3 represents the case of a human in a Context communicating with a Machine, e.g., an information service, in another Context. In this case the Machine communicates with the human by sensing and actuating audio-visual information, but the communication between the Machine and #3 may use a different communication protocol. The payload used to communicate is the “Portable Avatar” defined as a Data Type specified by the MPAI-PAF standard representing an Avatar and its Context.

Communication between the human in #1 and the Machine is based on raw audio-visual communication while communication between Machine and Entity #3 is carried out using a Portable Avatar .

Read a collection of usage scenarios.

The name of the standard is Human and Machine Communication (MPAI-HMC). It is published as a draft with a request for Community Comments, the last step before publication. Comments are due by 2024/02/19T23:59 UTC to secretariat@mpai.community.

To explain the second reason why the 40th General Assembly is a remarkable moment we have to recall that most MPAI application standards are based on the notion of AI Workflow (AIW) composed of interconnected AI Modules (AIM) executed in the AI Framework (AIF) specified by the MPAI-AIF standard. Four out of five documents are now  published in a new format where the Use Cases-AI Modules- Data Types chapters make reference to a common body of AIMs and Data Types.

Component-based software engineering aims to build software out of modular components. MPAI is implementing this notion in the world of standards.

See the links below and enjoy:

MPAI-HMC: https://mpai.community/standards/mpai-hmc/mpai-hmc-specification/

MPAI-MMC: https://mpai.community/standards/mpai-mmc/mpai-mmc-specification/

MPAI-OSD: https://mpai.community/standards/mpai-osd/mpai-osd-specification/

MPAI-PAF: https://mpai.community/standards/mpai-paf/mpai-paf-specification/


MPAI publishes 5 documents: 1 draft for community comments, 3 extensions, and 1 new standard

Geneva, Switzerland – 24 January 2024. MPAI – Moving Picture, Audio and Data Coding by Artificial Intelligence – the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 40th General Assembly (MPAI-40) approving the publication of a range of standards covering disparate technologies and application domains.

Human and Machine Communication (MPAI-HMC) is a draft published for Community Comments, the last step before publication. It includes a wide range technologies available from existing MPAI standards to enable an Entity, i.e., a human or a machine, to hold a communication with Entities as humans do. Comments are due by 2024/02/19T23:59 UTC to secretariat@mpai.community.

The newly-approved Object and Scene Description  (MPAI-OSD) V1.0 standard provides important technologies enabling the digital representation of position and orientation of Audio and Visual Objects and their combinations in Scenes. The MPAI-OSD capabilities enhance usability of the new Multimodal Conversation (MPAI-MMC) V2.1 and Portable Avatar Format (MPAI-PAF) V1.1.

MPAI Metaverse Model – Architecture (MPAI-MMM) V1.1 updates the MMM- Architecture Metadata to streamline communication between the Processes of a Metaverse Instance and uses the new MPAI-MMM Scripting Language (MMM-Script) to represent a wide range of use cases.

MPAI is now offering an innovative way to access to its new standards via the web:

MPAI-HMC: https://mpai.community/standards/mpai-hmc/mpai-hmc-specification/

MPAI-MMC: https://mpai.community/standards/mpai-mmc/mpai-mmc-specification/

MPAI-OSD: https://mpai.community/standards/mpai-osd/mpai-osd-specification/

MPAI-PAF: https://mpai.community/standards/mpai-paf/mpai-paf-specification/

MPAI is continuing its work plan that involving the following activities:

  1. AI Framework (MPAI-AIF): reference software, conformance testing, and application areas.
  2. AI for Health (MPAI-AIH): reference model and technologies for a system enabling clients to improve models processing health data and federated learning to share the training.
  3. Context-based Audio Enhancement (CAE-DC): new projects are brewing.
  4. Connected Autonomous Vehicle (MPAI-CAV): Functional Requirements of the data used by the MPIA-CAV – Architecture standard.
  5. Compression and Understanding of Industrial Data (MPAI-CUI): preparation for an extension to existing standard that includes support for more corporate risks.
  6. Human and Machine Communication (MPAI-HMC): model and technologies enabling a human or a machine to communicate with a machine or a human in a different cultural environment.
  7. Multimodal Conversation (MPAI-MMC): drafting reference software and conformance testing, and exploring new areas.
  8. MPAI Metaverse Model (MPAI-MMM): reference software and metaverse technologies requiring standards.
  9. Neural Network Watermarking (MPAI-NNW): reference software for enhanced applications.
  10. Portable Avatar Format (MPAI-PAF): reference software, conformance testing and new areas.
  11. End-to-End Video Coding (MPAI-EEV): video coding using AI-based End-to-End Video coding.
  12. AI-Enhanced Video Coding (MPAI-EVC). video coding with AI tools added to existing tools.
  13. Server-based Predictive Multiplayer Gaming (MPAI-SPG): technical report on mitigation of data loss and cheating.
  14. XR Venues (MPAI-XRV): development of the standard.

Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members.

Please visit the MPAI website, contact the MPAI secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.

 


MPAI publishes Context-based Audio Enhancement and Object and Scene Description for Community Comments

Geneva, Switzerland – 20 December 2023. MPAI, Moving Picture, Audio and Data Coding by Artificial Intelligence, the international, non-profit, and unaffiliated organisation developing AI-based data coding standards has concluded its 39th General Assembly (MPAI-39) approving the publication of the Context-based Audio Enhancement standard and Object and Scene Description standard for Community Comments.

The draft of the Context-based Audio Enhancement (MPAI-CAE) Version 2.1 standard enhances the compatibility of the Audio with the Visual and the Audio-Visual Scene Description specified by the draft Object and Scene Description (MPAI-OSD) standard. Both are published with requests for Community Comments. These are due by 2024/01/23T23:59 UTC and 17T23:58 UTC, respectively, to secretariat@mpai.community.

MPAI is continuing its work plan that involving the following activities:

  1. AI Framework (MPAI-AIF): reference software, conformance testing, and application areas.
  2. AI for Health (MPAI-AIH): reference model and technologies for a system enabling clients to improve models processing health data and federated learning to share the training.
  3. Context-based Audio Enhancement (CAE-DC): new projects are brewing.
  4. Connected Autonomous Vehicle (MPAI-CAV): Functional Requirements of the data used by the MPIA-CAV – Architecture standard.
  5. Compression and Understanding of Industrial Data (MPAI-CUI): preparation for an extension to existing standard that includes support for more corporate risks.
  6. Human and Machine Communication (MPAI-HMC): model and technologies enabling a human or a machine to communicate with a machine or a human in a different cultural environment.
  7. Multimodal Conversation (MPAI-MMC): drafting reference software and conformance testing, and exploring new areas.
  8. MPAI Metaverse Model (MPAI-MMM): reference software and metaverse technologies requiring standards.
  9. Neural Network Watermarking (MPAI-NNW): reference software for enhanced applications.
  10. Portable Avatar Format (MPAI-PAF): reference software, conformance testing and new areas.
  11. End-to-End Video Coding (MPAI-EEV): video coding using AI-based End-to-End Video coding.
  12. AI-Enhanced Video Coding (MPAI-EVC). video coding with AI tools added to existing tools.
  13. Server-based Predictive Multiplayer Gaming (MPAI-SPG): technical report on mitigation of data loss and cheating.
  14. XR Venues (MPAI-XRV): development of the standard.

Legal entities and representatives of academic departments supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data can become MPAI members.

Please visit the MPAI website, contact the MPAI secretariat for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media: LinkedIn, Twitter, Facebook, Instagram, and YouTube.