MPAI publishes Version 2 Audio Enhancement for Community Comments and the Neural Network Watermarking Reference Software

February 25, 2023
Top Quote The international, non-profit, unaffiliated Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) standards developing organisation has concluded its 29th General Assembly (MPAI-29) approving a new version of its Audio Enhancement (MPAI-CAE) Technical Specification posted for Community Comments and the Neural Network Watermarking (MPAI-NNW) Reference Software. End Quote
  • (1888PressRelease) February 25, 2023 - Geneva, Switzerland – The international, non-profit, unaffiliated Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) standards developing organisation has concluded its 29th General Assembly (MPAI-29) approving a new version of its Audio Enhancement (MPAI-CAE) Technical Specification posted for Community Comments and the Neural Network Watermarking (MPAI-NNW) Reference Software.

    Version 2 of the Context-based Audio Enhancement (MPAI-CAE https://mpai.community/standards/mpai-cae/) Technical Specification, besides supporting the functionalities of Version 1, specifies new technologies to enable a device to describe an audio scene in terms of audio objects and their directions. MPAI uses this Technical Specification to enable human interaction with autonomous vehicles, avatar-based videoconference and metaverse applications. The document is posted with a request for Community Comments to be sent to secretariat ( @ ) mpai dot community until the 20th of March 2023 dot

    The Reference Software of Neural Network Watermarking (MPAI-NNW https://mpai.community/standards/mpai-nnw/) provides the means, including the software, to evaluate the performance of neural network-based watermarking solutions in terms of imperceptibility, robustness, and computational cost. The version of the software is specific for image classification but can be extended to other application areas.

    MPAI is continuing its work plan including the development of the following Technical Specifications:

    1) AI Framework (MPAI-AIF https://mpai.community/standards/mpai-aif/). Standard for a secure AIF environment executing AI Work-flows (AIW) composed of AI Modules (AIM).
    2) Avatar Representation and Animation (MPAI-ARA https://mpai.community/standards/mpai-ara/ ). Standard for generation and anima-tion of interoperable avatar models reproducing humans and expressing a Personal Status.
    3) Multimodal Conversation (MPAI-MMC https://mpai.community/standards/mpai-mmc). Standard for Personal Status generalising the no-tion of Emotion including Cognitive State and Social Attitude.

    The MPAI work plan also includes exploratory activities, some of which are close to becoming standard or technical report projects:

    1) AI Health (MPAI-AIH https://mpai.community/standards/mpai-aih). Targets an architecture where smartphones store users’ health data processed using AI and AI Models are updated using Federated Learning.
    2) Connected Autonomous Vehicles (MPAI-CAV https://mpai.community/standards/mpai-cav). Targets the Human-CAV Interaction En-vironment Sensing, Autonomous Motion, and Motion Actuation subsystems implemented as AI Workflows.
    3) End-to-End Video Coding (MPAI-EEV https://mpai.community/standards/mpai-eev). Extends the video coding frontiers using AI-based End-to-End Video coding.
    4) AI-Enhanced Video Coding (MPAI-EVC https://mpai.community/standards/mpai-evc). Improves existing video coding with AI tools for short-to-medium term applications.
    5) Server-based Predictive Multiplayer Gaming (MPAI-SPG https://mpai.community/standards/mpai-spg). Uses AI to train neural net-works that help an online gaming server to compensate data losses and detects false data.
    6) XR Venues (MPAI-XRV https://mpai.community/standards/mpai-xrv). Identifies common AI Modules used across various XR-enabled and AI-enhanced use cases where venues may be both real and virtual.

    It is still a good opportunity for legal entities supporting the MPAI mission and able to contribute to the development of standards for the efficient use of data to join MPA (https://mpai.community/how-to-join/join/).

    Please visit the MPAI web site (https://mpai.community/), contact the MPAI secretariat (secretariat ( @ ) mpai dot community) for specific information, subscribe to the MPAI Newsletter and follow MPAI on social media:
    - LinkedIn (https://www.linkedin.com/groups/13949076/)
    - Twitter (https://twitter.com/mpaicommunity)
    - Facebook (https://www.facebook.com/mpaicommunity) ,
    - Instagram (https://www.instagram.com/mpaicommunity/)
    - YouTube (https://youtube.com/c/mpaistandards).

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