Making Every Lesson Available in the Language and Format a Student Actually Needs
English language learners and students with reading related learning differences are frequently served the exact same static, text only materials as everyone else, even though institutions know accessible, multilingual support meaningfully improves outcomes.
Why this keeps costing you
Building and staffing separate accessible or multilingual tracks for every language and format an institution serves is rarely realistic at scale, which means the students who would benefit most from a different format often simply do not get one.
How we build it
The same text to speech and speech to text pipelines already built for the language assessment platform's speaking and listening modules are applied here to course materials and instructions rather than test content, so reading material can be heard aloud and verbal responses can be captured and transcribed for assignments that would otherwise require typed text. A translation layer sits on top of the same content, so a lesson can be delivered in a student's stronger language without an institution building and maintaining a separate parallel course for every language it needs to support.
What this looks like once it is running
- 1Text to speech for reading materials and instructions
- 2Speech to text for verbal responses and assessments
- 3Multi language support layered across core course content
- 4A consistent experience whether a student works in text, voice, or a blend of both
- 5Works alongside existing tutoring and assessment tools rather than as a separate system
Institutions expand access without a proportional increase in staff or content production effort, seeing stronger engagement from English language learners and students who benefit from an alternative format, running one unified platform instead of parallel systems per language.
For more details, click the relevant case study link below.
View AI Coach Platform case studyMulti-modal Assessment (AI Assessment Platform)
This reuses the text to speech and speech to text infrastructure already live inside Zaltech's AI Assessment Platform, built originally for integrated testing across all language skills, extended here from assessment content to everyday course materials. The same speech pipelines that score a spoken language test power a student simply hearing a reading assignment read aloud.
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02Testing Every Language Skill at Once, and Grading All of Them Instantly
Speaking scored from streamed audio against a spoken-assessment rubric, listening prompts generated by TTS, and all four modules writing into one scoring engine.
03One Tutor Per Student, Without Hiring One Tutor Per Student
Coaches grounded in the institution's own curriculum and explanation style, across chat, audio and video, adapting pacing to each student's real performance over time.
Want this one built for your business?
We will walk you through the architecture, what it takes to integrate with your systems, and a realistic timeline — before anyone signs anything.