Tasks

Explore the phonetic recognizer of the Rhubarb Lip Sync project and check whether its algorithms or ideas can be used for decoding an audio track into letters/phonemes/syllables in the "Uchitsya legko" project.

Create and grow the "Learn is Easy!" Telegram channel as a living layer around the product: for user retention, spreading useful mechanics, viral growth, feedback, and showcasing the project's development.

Develop and implement a subscription to "Learning is Easy!" updates as a mechanism for user retention and re-engagement.

Add convenient content and mechanic sharing for "Learn is Easy!" to support organic and viral distribution.

Design a universal questioning mechanic that helps explore objects and phenomena across different domains and complexity levels.

Design the main page as a feed of increasing complexity and domain depth, where users naturally find their relevant level without prior segmentation.

Define and implement the next level after mastering words: reading sentences taking into account the structure of written utterances, punctuation, pauses, and intonation.

Add standard Web Push with VAPID so that users with the "I am online" status receive notifications about new requests even when the tab is closed.

Implement the "Ask for help" / "I'm online" flow with quick response, text communication, and a built-in call.

Capture and develop the idea of instructors as a separate layer of the platform alongside independent learning mechanics.

Set up a custom controlled TTS process to pre-generate audio for letters, syllables, and words instead of relying on unpredictable browser SpeechSynthesis.

Create game voice characters with different speech rate and pitch settings so children can choose a comfortable option, and add a custom character builder.

Recognize short spoken answers from a child using the Web Speech API in "What is shown in the picture?" tasks.

Use the Web Speech API to play educational units: letters, syllables, and individual words.

Test whether parametric speech synthesis can be used for reading instruction: individual Russian sounds as states, and their combinations as controlled transitions.

Check whether the mechanism helps the child recover a previously unseen word, rather than just memorizing studied examples.

Implement a working interactive prototype that goes through a single complete learning cycle without unnecessary platform infrastructure.

Determine which connections the system considers mastered and when it can hide the image, sound, or spelling.

Put together a compact learning set to test the transfer of letter correspondences to new words.