Pronunciation Codes provide a visual and auditory way to show how graphemes and phonemes connect, using a consistent framework.
 

Pronunciation Codes can be produced within all languages that use an alphabetic writing system where:
 

• letters a–z are used

• those letters, alone or in combinations such as digraphs, represent speech sounds
   

Examples include:

• English

• Spanish

• French

• German

• Italian

• Finnish

• Turkish

• Dutch

• Swedish

• Norwegian
   

Learners who are learning to speak, read or write in these languages benefit from a flexible system for real speech that extends phonetic symbols to show sounds and how they map to graphemes.
 

For example, in Italian, casa is shown as <c> <a> <s> <a>, with phonetic symbols /ˈka.za/, so users can see how the graphemes map to the sounds.
 

Although there are regional and individual variations in spoken language, Pronunciation Codes can be used by a wide range of people for different purposes. We can have an Italian Pronunciation Code and others, in addition to the English Pronunciation Code, as part of a set of International Pronunciation Codes.
 

This supports users in understanding how speech and print connect in a way that works for them.
 

Types of Pronunciation Code in use today

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English Pronunciation Code (EPC)
 

The English Pronunciation Code aligns with the British IPA but has been extended and adapted to bridge speech and print.

It makes the structure of spoken English visible in a way that connects directly to written words.
 

Phonics Pronunciation Code (PPC)
 

The Phonics Pronunciation Code centres on phonics programmes and shows the expected links as specified by programme developers.

This may also change grapheme segmentation. For example:

• some define nk as a grapheme: r i nk

• others align more closely with DfE guidance, mapping sounds to their own grapheme where possible: n i n k

The PPC makes these programme-based decisions visible.
 

Personal Pronunciation Code
 

The Personal Pronunciation Code is the brain's internal connection between graphemes and their sound values.

This can differ from both the PPC and the EPC when speaking English.

It reflects how the individual is actually connecting speech and print.
 

The underlying system
 

Underneath the technology that shows these codes sits Emma Hartnell-Baker’s Code Mapping® algorithm. For axample an English Code Overlay (ECO) can be used.
 

This proprietary algorithm segments words into structured phoneme and grapheme arrays, enabling precise alignment between speech and print by making each correspondence visible and manipulable.
 

Hartnell-Baker and her team have achieved something no-one else has been able to do: a system that makes the full structure of words visible and usable in real time. It reflects her AuDHD, pattern-seeking, prediction-driven brain, which identifies logic and consistency where others experience English orthography as complex or chaotic.
 

This is not a static representation of language. It is a dynamic system that allows correspondences to be mapped and adjusted across:

• different languages

• different accents

• different pronunciation patterns

This opens up powerful new possibilities.
 

It enables the development of technology that shows the full code of written language directly to the user, supporting independent access to reading, spelling, and communication. This includes self-teaching readers who can explore and secure the structure of words for themselves.

Illiteracy is a trillion-pound global problem. Hartnell-Baker’s position is that it does not have to be, even when the orthography is opaque. 
 

When children are given access to clear speech–print mapping, especially between birth and age seven, when the brain is most plastic and attuned to the sounds of language, learning becomes significantly easier.
 

By making these relationships explicit and accessible, the Code Mapping® algorithm underpins Pronunciation Codes and offers a scalable way to support literacy, communication, and learning for all, with the potential to tackle some of the world’s most difficult problems at scale. We are developing the Self-Teaching Reader than enables users, including those who are dyslexic, to determine the English code level level they support they need using My Reading Finger.  

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Integral to phonics reform in England is an awareness of variation, and an understanding that the information introduced by programmes in a classroom setting, led by a human, may not be the most effective way to eradicate illiteracy.

Few humans have the knowledge of how speech and print connect for individuals, or how to offer targeted support that resolves accent variation. Nor do they have the ability to provide the mapping of words to all children in real time, as and when it is needed. 

PRE was formed by specialists in SEN, SpLD, SALT and TESOL to create scalable word mapping solutions for all learners, including those who are non-speaking and those who do not speak English as their first language, freeing up teachers to focus on fluency, vocabulary and comprehension, and igniting a passion for the written word.