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Breaking Digital Language Barriers: CDLI at the India AI Impact Summit 2026

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Dr. Richard Cave, Co-Director of the Centre for Digital Language Inclusion (CDLI), represented CDLI as a guest of the British Council at the India’s AI Summit in Delhi.

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27 Feb 26
Harrison Kamau

Dr. Richard Cave, Co-Director of the Centre for Digital Language Inclusion (CDLI), represented CDLI as a guest of the British Council at the India’s AI Summit in Delhi – an event attended by over 70,000 people. Richard discussed a message that resonated deeply with the diverse audience: AI-driven speech recognition technology must be inclusive in every language and better recognising people with impaired speech.

CDLI's work addresses a critical gap: while speech recognition and natural language processing have made remarkable strides, these advances frequently do not benefit those with speech difference. This includes millions of people globally who live with Cerebral Palsy, Head and Neck Cancer, MND/ALS, Trauma, Down Syndrome amongst many other conditions.

CDLI is building speech recognition models that are trained on inclusive datasets that better recognise diverse speech patterns. What makes CDLI's work particularly powerful is its commitment to open-source principles. By publishing datasets and models freely, researchers and developers worldwide can build upon this foundation, accelerating progress and ensuring that language inclusion becomes a shared and achievable mission.

During the sessions, Dr Cave discussed the work of CDLI with the UK High Commissioner to India, Lindy Cameron CB OBE.

“The audience was wonderful and reminded me that Inclusive speech recognition models are for everyone and everywhere, and there are so many conversations to have and to be understood - in India and the world.”

Dr Richard Cave.

When people with impaired speech are better understood in daily life, it builds opportunity. In education, work healthcare, social networks financial services, and autonomy. Voice-enabled interfaces that work for everyone can lower literacy barriers and increase opportunity.

This initiative is led by UCL’s Global Disability Innovation Hub supported by google.org and UK International Development funded AT2030 Programme. The Centre for Digital Language Inclusion works in collaboration with local and international partners. Technical support has been provided by Modal, whose GPU sponsorship is powering the development of the ASR models. Other collaborators include The Research Center Trustworthy Data Science and Security, Talking Tipps Africa Foundation, Senses Hub, University of Ghana, Strathmore University, Hogan Lovells.

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27 Feb 26
Harrison Kamau

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Accessibility
Accessibility, A11y
The design of technologies, services, and environments so they can be used by people with diverse abilities, including people with disabilities.
Assistive Technology
Assistive Technology
Tools or systems that help people with disabilities perform tasks more easily. Inclusive speech recognition can function as assistive technology for communication.
Automatic Speech Recognition (ASR)
Automatic Speech Recognition (ASR), Automatic Speech Recognition, ASR
Technology that converts spoken language into written text. ASR enables devices and software to "understand" human speech and is used in tools such as voice assistants, transcription services, and accessibility technologies.
Community-Centred Design
Community-Centred Design, Community Centred Design
An approach that actively involves people who will use the technology in its design, development, and testing, ensuring solutions reflect real needs and lived experiences.
Data Annotation
Data Annotation
The process of labelling speech recordings with accurate text or metadata. Annotation helps machines learn how spoken words relate to written language.
Digital Language Inclusion
Digital Language Inclusion
The practice of ensuring that digital technologies recognise, understand, and support all ways people speak, including diverse languages, accents, and speech patterns.
Ethical Data Collection
Ethical Data Collection
The practice of collecting data with informed consent, transparency, privacy protection, and respect for participants' rights and dignity.
Inclusive AI
Inclusive AI
Artificial Intelligence systems designed to work fairly and effectively for people of different abilities, languages, and backgrounds, without excluding or disadvantaging certain groups.
Machine Learning
Machine Learning
A branch of AI that allows computer systems to learn patterns from data and improve their performance over time without being explicitly programmed for every task.
Non-Standard Speech
Non-Standard Speech
Speech that differs from what most speech recognition systems are trained on. This may include speech affected by disability, neurological conditions, injury, accent variation, or local language patterns.
Open-Source
Open-Source, opensource, open source
Software, data, or models that are freely available for anyone to use, study, modify, and share. CDLI promotes open-source approaches to accelerate inclusive innovation.
Speech Dataset
Speech Dataset
A structured collection of recorded speech samples and corresponding text. These datasets are used to train and improve speech recognition models.
Speech Impairment
Speech Impairment
A condition that affects a person's ability to produce clear or typical speech. This can be temporary or lifelong and may result from disability, illness, injury, or neurological differences.
Speech Model
Speech Model
A trained AI system that processes and recognises spoken language. Speech models improve as they are exposed to more diverse and representative speech data.
Under-Resourced Languages
Under-Resourced Languages, Under Resourced Languages
Languages that lack sufficient digital data, tools, or technological support. Many African languages fall into this category, making them poorly supported by mainstream speech technologies.