Speech processing
Each reading goes through open speech-recognition software that READSmart runs in its own container on GPU servers rented from RunPod: Silero VAD finds the speech, OpenAI Whisper (the downloadable model, size “medium”) writes the transcript, and WhisperX lines each word up with the audio. The audio is not sent to a speech-recognition company's service.
The container fetches the audio through a private link that works for at most 15 minutes, along with the passage text, grade and language. It never receives a name, username or email, but the storage path and record numbers it uses contain internal numbers for the school, reading session and pupil. It deletes its copy of the audio as soon as the reading has been processed.
What the scores mean
- READSmart compares the transcript with the passage and highlights words that differ. These highlights are text differences, not a judgement of pronunciation. READSmart does not detect mispronunciations.
- A small calibration formula corrects the automated WCPM and accuracy toward teachers' scores, using grade and language. It is fitted from results and teacher scores, never from voices.
- Comprehension answers are marked against an answer key. No AI marks them.
- READSmart only suggests a Phil-IRI level. The teacher listens and decides. No decision about a pupil is made by a computer alone.
Practice stories written by AI
When a pupil asks for a story, READSmart first checks the topic. It must be 2 to 60 letters and at most 8 words, and topics with names, personal details or unsafe words are refused before anything is saved. The story is then made through Cloudflare Workers AI:
- Mistral Small 3.1 writes the story from the topic, grade and language.
- Llama 3.3 70B gives it a title, checks its facts and writes comprehension questions.
- Llama Guard 3 checks the story for unsafe content.
- FLUX.2 [klein] 9B draws a picture from a short scene description, copying the drawing style of two of READSmart's own sample pictures, and Llama 4 Scout checks the picture against the story.
Only the writing model receives the pupil's topic, and no model receives the pupil's name or account. Cloudflare states that it does not use customer content to train AI models. Our AI Gateway keeps usage records (the step, grade, language and a random request number) without the prompts, stories or pictures. The picture step can't go through the gateway, so it goes to Workers AI directly, and READSmart counts those picture requests in its own records instead.
A teacher must approve every story before any pupil can read it. The teacher sees warnings from the fact check, can use a plain placeholder instead of the picture, and can hide or retire the story. A topic that passes the first check is saved with the request even if no story is made.