Audio AI Working Group

Updated Feb 11, 2026 Audio AI

1. Introduction

  • 1.1. Work Group Mission Statement: 

Create a central hub for audio applications on edge devices, fostering innovation, collaboration, and standardization.

  • 1.2. Key Definitions: 
  • Innovation Hub: Drive innovation by focusing on cutting-edge audio technologies and applications.
  • Collaboration: Facilitate collaboration among industry leaders, researchers, and developers to share knowledge and best practices.
  • Standardization: Develop and promote standards for audio processing on edge devices, ensuring compatibility and interoperability.
  • Resource Pooling: Centralize resources, models, tools, and expertise to simplify the development and deployment of audio applications.
  • 1.3. Purpose:
    • Innovation in Audio Applications:
      • Encourage the development of new audio technologies and applications for edge devices.
      • Promote research and development in audio signal processing, machine learning, and AI for audio.
    • Collaboration and Networking:
      • Enable partnerships between industry, academia, and other stakeholders.
      • Organize regular meetings, workshops, and conferences to share knowledge and best practices.
      • Collaborate with other WG within EAIF in overlapping areas.
    • Standardization and Best Practices:
      • Define Audio application for Edge AI.
      • Develop and promote standards for audio applications in edge devices.
      • Create guidelines and best practices for the implementation and deployment of audio technologies.
    • Education and Training:
      • Provide training and resources for developers and engineers working on audio applications.
      • Develop educational materials in forms of blogs/articles/courses to support the community.
      • Lectures and panels on Edge AI Foundation events.
  • 1.4. Deliverables:
    • Educational Content:
      • Tutorials, webinars, and seminars covering foundational and advanced topics in Audio for Edge AI.
      • Whitepapers, blogs and reports detailing industry trends, research advancements, and best practices in audio domain.
    • Community Engagement Activities:
      • Roundtable discussions to foster dialogue between academia, industry, and individual contributors.
      • Networking events to build relationships and encourage collaboration.
      • Set up Discord channel to share updates, have discussions and answer related questions by the community. 
      • Conduct a survey to gather input from the community on standardization needs and priorities.
  • Knowledge Dissemination:
    • Regular updates on breakthroughs, tools, and technologies in Edge AI and Generative AI.
    • Curated newsletters summarizing key developments and insights.
  • Recognition and Amplification:
    • Case studies and success stories showcasing member contributions and achievements.
    • Spotlight series on individuals and organizations advancing the field.
  • Practical Resources:
    • Demonstrations and walkthroughs of innovative Edge AI and Generative AI solutions in audio domain.
    • Open-access repositories for tools, datasets, and frameworks.
  • Future-Oriented Initiatives:
    • A dynamic and evolving definition of audio for Edge AI that reflects current advancements.
    • Strategic plans to attract new participants and foster innovation in the community.
    • Form a subcommittee to work on developing standards and best practices for audio applications in edge devices
  • Collaborative Publications:
    • Co-authored articles, research papers, or blog posts between academic and industry members.
    • Annual reviews summarizing the group’s impact and the field’s progress.
  • 1.5. Target Audience: 

Researchers and developers from industry, academia and individuals which have interest in audio domain applications for edge AI. 

2. Foundational Principles

  • 2.1. Shared Vision & Goals:
    • Identify key industry challenges and opportunities in Edge AI audio applications. Set specific, measurable objectives that address these needs, such as improving audio signal processing accuracy or reducing latency in edge devices.
    • Organize vision-setting workshops where members can collaboratively outline long-term goals and aspirations for audio technologies in Edge AI.
  • 2.2. Open Communication & Transparency:
    • Promote regular and open communication channels (e.g., meetings, workshops, online forums). 
    • Include a note taker (we use Fathom and we will have a WG note taker who should be included in the WG meeting invites.) 
    • Establish clear protocols for data sharing, intellectual property (IP) protection, and publication if needed.
  • 2.3. Trust & Collaboration:
    • Work Group leads should foster an environment of trust and mutual respect between academic and industry partners.
    • And encourage active listening, constructive feedback, and shared decision-making.
  • 2.4. Diversity & Inclusion:
    • Champion diversity in team composition to foster innovation and broader perspectives.

3. Collaborative Research & Development

  • 3.1. Data Sharing & Access:
    • Best practices for data collection, annotation, and sharing, considering privacy, security, and ethical concerns.
    • Mechanisms for data access control and usage agreements, if needed.
  • 3.2. Technology Transfer & Commercialization:
    • Strategies for translating research findings into commercial products and services.
    • Mechanisms for IP protection and licensing.
    • Supporting entrepreneurship and startup creation.
  • 3.4. Talent Development & Training:
    • Programs for student internships, joint research projects, and faculty exchanges.
    • Opportunities for professional development and upskilling for researchers and industry professionals.

4. Ethical Considerations

  • 4.2. Fairness & Bias:
    • Addressing potential biases in AI algorithms and ensuring fair and equitable outcomes for all users.
    • Developing and implementing responsible AI practices.
    • More?
  • 4.3. Societal Impact:
    • Considering the broader societal implications of Edge AI technologies.
    • Mechanisms for engaging with stakeholders and addressing ethical concerns.

5. Tools & Technologies

  • 5.1. Hardware & Software Tools:
    • Work Group should consider if access to hardware and software tools for research and development are needed for any deliverables.

6. Evaluation & Assessment

  • 6.1. Metrics for Success:
    • Number of New Projects and Innovations:
      • Track the number of new audio projects and innovations initiated within the WG.
      • Set a target for the number of new projects per year.
    • Collaboration Metrics:
      • Measure the number of partnerships and collaborations formed.
      • Qualify of partnerships and collabs based on their output (scope, innovation, relevance)
      • Track participation in meetings, workshops, and conferences.
    • Standardization Achievements:
      • Monitor the development and adoption of new standards and best practices.
      • Set targets for the number of standards developed and adopted annually.
    • Educational Impact:
      • Track the number of training sessions, workshops, and courses conducted.
      • Measure the number of participants and their feedback.
    • Community Engagement:
      • Monitor the growth of the WG community through membership and participation metrics.
      • Track engagement on online platforms and forums.