This standard adopts MPAI Technical Specification Version 1.2 as an IEEE Standard. Multimodal Conversation (MPAI-MMC) is an MPAI Standard comprising five use cases, all sharing the use of artificial intelligence (AI) to enable a form of human-machine conversation in completeness and intensity.
- Sponsor Committee
- BOG/CAG - Entity Collaborative Activities Governance Board
- Status
- Active Standard
- PAR Approval
- 2022-09-21
- Board Approval
- 2022-12-03
- History
-
- Published:
- 2023-04-28
Working Group Details
- Society
- IEEE SA Board of Governors
- Sponsor Committee
- BOG/CAG - Entity Collaborative Activities Governance Board
- Working Group
-
MMCWG - Multimodal Conversation Working Group
- IEEE Program Manager
- Jonathan Goldberg
Contact Jonathan Goldberg - Working Group Chair
- Stephen Dukes
Other Activities From This Working Group
Current projects that have been authorized by the IEEE SA Standards Board to develop a standard.
P3300
IEEE Draft Standard - Adoption of Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Technical Specification Multimodal Conversation (MMC) Version 2
Multimodal Conversation (MPAI-MMC) specifies: 1.tData Formats for analysis of text, speech, and other non-verbal components as used in human-machine and machine-machine conversation applications. 2.tUse Cases implemented in the AI Framework using Data Formats from MPAI-MMC and other MPAI standards and providing recognized applications in the Multimodal Conversation domain. This Technical Specification includes the following Use Cases: 1.tConversation with Personal Status (CPS), enabling conversation and question answering with a machine able to extract the inner state of the entity it is conversing with and showing itself as a speaking digital human able to express a Personal Status. By adding or removing minor components to this general Use Case, five Use Cases are spawned: 2.tConversation About a Scene (CAS) where a human converses with a machine pointing at the objects scattered in a room and displaying Personal Status in their speech, face, and gestures while the machine responds displaying its Personal Status in speech, face, and gesture. 3.tVirtual Secretary for Videoconference (VSV) where an avatar not representing a human in a virtual avatar-based video conference extracts Personal Status from Text, Speech, Face, and Gestures, displays a summary of what other avatars say, and receives and act on comments. 4.tHuman-Connected Autonomous Vehicle Interactionu201d (HCI) where humans converse with a machine displaying Personal Status after having been properly identified by the machine with their speech and face in outdoor and indoor conditions while the machine responds by displaying its Personal Status in speech, face, and gesture. 5.tConversation with Emotion (CWE), supporting audio-visual conversation with a machine impersonated by a synthetic voice and an animated face. 6.tMultimodal Question Answering (MQA), supporting request for information about a displayed object. 7.tThree Uses Cases supporting text and speech translation applications. In each Use Case, users can specify whether speech or text is used as input and, if it is speech, whether their speech features are preserved in the interpreted speech: 7.1.tUnidirectional Speech Translation (UST). 7.2.tBidirectional Speech Translation (BST). 7.3.tOne-to-Many Speech Translation (MST). 8.tThe u201cPersonal Status Extraction Composite AIMs that estimates the Personal Status Conveyed by Text, Speech, Face, and Gesture u2013 of a real or digital human.
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