Inaugural International Workshop on Rethinking Children's Automatic Speech Recognition (ASR) for Education

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In K–12 education, Automatic Speech Recognition (ASR) is increasingly being applied to support learning, engagement, and accessibility. However, developing ASR systems for children continues to poses monumental challenges, especially considering the stringent requirement resulting from various use cases in children’s education settings. Moreover, representative speech datasets from these populations are particularly scarce, while data collection is further complicated by ethical considerations such as privacy and informed consent.

Workshop Sponsors

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Inaugural Workshop Chairs

Portrait of Jinjun Xiong.
Portrait of Jing Liu.

Workshop Goals

This invitation only workshop provides a timely forum for interested stakeholders to come together to:

  • Assess the state-of-the-art in children’s ASR
  • Find a common ground in our collective understanding of the needs and challenges of children’s ASR in education
  • Share lessons and best practices
  • Standardize evaluation and benchmarking methodologies
  • Charter new (or call-for-attention to important) research directions
  • Build a coalition of shared minds to collectively address those challenges for the better development of children’s ASR for education settings

We invite participants from multidisciplinary communities, to join this discussion including educators, policymakers, ed-tech entrepreneurs, speech researchers, AI-ML experts, data scientists and linguists. Given your expertise in this area, we invite you to contribute to topics relevant to this workshop, including, but not limited to:

  • Diversity and quality of existing public children’s speech data sets
  • Ontology development for children’s speech datasets
  • Equipment and systems for children’s speech data collection
  • Evaluation methodologies for existing ASR systems on children’s speech
  • Needs for multi-level ASR systems for children’s speech
  • Educational applications spanning age groups, subject areas, language learning contexts, and delivery formats (e.g., in-person vs. virtual)
  • Initiatives and requirements for making proprietary children’s speech data publicly accessible
  • Current benchmark creation and dataset design efforts advancing ASR for children’s speech
  • Privacy-preserving ASR and edge ASR

This workshop presents an exceptional opportunity for an interdisciplinary, cross-sector community to collectively shape the future of children’s ASR technologies in education. Together, we aim to develop novel AI solutions that can help improve learning outcomes for all students. Your participation and contribution will enrich these discussions and amplify our collaborative investment and efforts in building a better learning environment for our children.

Workshop Agenda

7:00 - 8:00

Breakfast and Sign-in

8:00 - 8:15

Welcome and Opening

UB Provost: Scott Weber

UB SEAS Dean: Kemper Lewis
Workshop Organizers:
Jinjun Xiong (UB) and Jing Liu (UMD)

8:15 - 9:00

Scope of the Workshop

Jinjun Xiong (UB)

9:00 - 10:00

Challenges in Children’s ASR,

Why Now?

Moderator: Jing Liu (UMD)

Panelists:
Abeer Alwan (UCLA)
Carol Espy-Wilson (UMD)
Matthew Perez (TeachFX)

ABSTRACT: Many assume that the challenges of ASR
for children have already been solved. But is it really
the case? Even with today’s advances in AI, significant
hurdles remain. What are the persistent technical and
practical obstacles? What innovative approaches might
address them? And how does an educational focus on
ASR technology influence these considerations?  In this
panel, experts with decades of experience in ASR will
share insights into these complex issues, shed light on
the roadblocks that still stand in the way, and offer
pathways that can lead to breakthroughs moving forward.

10:00 - 10:15

Coffee Break

 

10:15 - 11:15

Data Drives True AI, but Where do We Stand Today?

Moderator: Rohini Srihari (UB)

Panelists:
Ahmed Attia (UMD) Mark Hasegawa-Johnson (UIUC)
Brian MacWhinney
(CMU)
Jacob Whitehill
(WPI)

ABSTRACT: The limited availability of open-source,
large-scale speech datasets from children remains a
major barrier to advancing AI-driven speech models
for education. Privacy concerns make the collection
and sharing of such data even more complex. This
panel will showcase teams that are actively tackling
these challenges by developing novel datasets of
children’s speech. Leading scholars will present
their approaches, share lessons learned and engage
with the community to chart a path toward building a
more robust data infrastructure, one that can accelerate
progress in children’s ASR for educational applications.

11:15 - 12:15

Needs and Solutions:
Users’ Perspectives

Moderator: Brian Graham
(Grand Island Central Schools)

Panelists:
Orna Azulay (Remote Speech)
Amy Armstrong (Summit)
Arun Ramanathan (PowerMyLearning)
Drew Shoaf (Magpie)

ABSTRACT: Many EdTech products rely on students’
voices as a primary input to power their core functionalities,
whether it’s assessing mathematical reasoning,
evaluating literacy development, or creating a seamless
user experience. However, the requirements for children’s
ASR vary widely depending on the subject domain,
student subgroups, and the specific goals of each product.
This panel brings together entrepreneurs from leading
EdTech companies to share how they incorporate ASR
into their tools, the unique needs and solutions they’ve
developed, and their aspirations for the future of the field.
The conversation is designed to spark greater alignment
between academic research, industry needs, and funders’
investments, and ensure that progress in children’s ASR
translates into meaningful impact in education.

12:15 - 1:15

LUNCH BREAK

 

1:15 - 2:15

Children’s ASR in Action
at National AI Institutes
and Centers

Moderator: Marisha Speights (Northwestern University)

Panelists:
Suma Bhat (Princeton)
Sidney DiMello
(University of Colorado-Boulder)
Lei Liu (ETS)
Wookhee Min (NCSU)

ABSTRACT: Two flagship federal initiatives are leading
the way in applying AI to education: the National AI Institutes
program and the National Research and Development
Centers on Using Generative Artificial Intelligence to
Augment Teaching and Learning in Classrooms (U-GAIN).
In this session, panelists representing these programs will
share real-world educational use cases from their institutes
and centers. They will discuss how children’s ASR is being
integrated into their work, highlight successes and
lessons learned, and reveal their “wish list” for
future advancements in children’s ASR technology.

2:15 - 3:15

Interests from Funding Agencies and their Perspectives on Children’s ASR for Education

Moderator: Dana Suskind
(University of Chicago)

Panelists:
Elizabeth Mokyr Horner (Gates Foundation)
Robert Ochsendorf
(NSF)
Katie Wetstone (DrivenData)

ABSTRACT: Funding plays a pivotal role in guiding the
research priorities and efforts of the community. As the
federal funding landscape evolves, support from
private-sector foundations will become increasingly
influential. In this discussion, program officers from
both a federal funding agency (NSF) and private
foundations will share their perspectives on the
importance of children’s ASR in education. They will
address its relevance within a broader, integrated
solutions context, highlighting complementary
technologies, and outline their “wish list” for
future technology and solution development.

3:15 - 3:30

Coffee Break

 

3:30 - 4:30

ASR and the Future
of Assessment

Moderator: Alison Hendricks (UB)

Panelists:
Nonye Alozie (SRI)
Lydia Liu (ETS)
Susan Lottridge (Cambium)
Kirk Vanacore (Cornell)

ABSTRACT: Assessment is one of the most dynamic
and promising frontiers for applying ASR in education.
By enabling more individualized evaluation, ASR has
the potential to transform traditional assessment systems
by moving beyond rigid, end-of-year standardized tests
toward approaches that are timely, adaptive and deeply
informative. This panel brings together experts from
leading assessment companies and research institutions
to explore both the technical and practical dimensions of
ASR-powered assessment. Together, they will share their
insights on current innovations and offer their
visions for the future of assessment in the age of AI.

4:30 - 5:30

Small Group Deep Dive

 
ABSTRACT: After a full day of inspiring talks and lively
conversations, attendees will have a chance to channel
their energy and ideas into focused discussions. In small,
topic-centered groups, participants will explore emerging
key themes during the day, identifying areas worth pursuing
beyond the event. Possible discussion topics include: (1)
Standardizing evaluation and benchmarking for tracking
progress in children’s ASR for education; (2) Sharing best
practices and lessons learned across the community; (3)
Coordinating collective data collection efforts to benefit
all stakeholders, and (4) Building a lasting coalition to
sustain momentum and drive continued impact.

5:30 - 6:15

Group Discussion for Next Steps

 
ABSTRACT: We will bring everyone back together to share
the key takeaways from each small-group discussion and
collaboratively outline a roadmap for moving forward.
To keep the momentum alive, we’ll conclude by inviting
enthusiastic volunteer writers to lead the development
of a white paper that captures our findings and
recommendations for the broader community.

6:15 - 6:30

Travel to Dinner

 

6:30 - 8:30

DINNER