Prepare your recitation for Murajaa Mobile
Upload a full-surah MP3, detect and review its ayah boundaries, then export a directly importable custom-reciter package — entirely in your browser.
What is this tool?
This tool turns a full-surah MP3 into a Murajaa Mobile custom-reciter package. The original audio stays as one continuous track, while a JSON timeline locates every ayah precisely.
Whether you recorded your own recitation or use a sheikh's recording, you can review every boundary before importing the result into the mobile app.
How to use it
Upload your audio
Drag and drop an MP3 file of a full surah recitation. The file stays on your device — nothing is uploaded to any server.
Select the surah
Choose which surah the audio corresponds to. The tool supports both Hafs and Warsh riwayat and knows the exact number of verses for each surah.
Detect or mark the verses
Auto-detect (recommended): The AI model transcribes the Arabic audio and matches it to the Quranic text to find each verse boundary automatically. The first time, it downloads a 131 MB model that is then cached for future use.
Manual mode: Listen to the audio and press Space each time an ayah ends. The current ayah is shown with Tajweed colors so you can place each timing marker accurately.
Adjust the markers
After detection or manual marking, fine-tune each ayah boundary with the +/- buttons. Preview each ayah range to verify its start and end, with adjustment precision down to 0.01s.
Export
Download SSS.zip containing exactly SSS.mp3 and SSS.json. Import that ZIP as a custom reciter in Murajaa Mobile; the JSON timeline drives ayah navigation without interrupting the continuous audio.
Key features
100% private
Everything runs locally in your browser. Your audio is never sent to any server. The AI model runs via WebAssembly on your device.
AI-powered verse detection
Uses NVIDIA's FastConformer CTC model, quantized for the browser. It transcribes Arabic speech and uses Levenshtein matching to align the transcription with the Quranic text.
Save your progress
Working on a long surah? Save your session as a draft and come back later. Your audio and markers are stored locally in IndexedDB.
Pre-trim
If your audio has an intro, outro, or unrelated content, set a start and end point and explicitly apply the trim before export. The resulting MP3 becomes the package audio.
Playback speed
Adjust playback speed from 0.25x to 3x. Useful for quickly reviewing long surahs or slowing down to catch precise verse endings.
Tajweed display
Verse text is displayed with Tajweed color coding during marking, so you can follow along with the recitation and know exactly where each verse ends.
Under the hood
The audio is resampled to 16 kHz, then processed in 30-second chunks through a mel spectrogram and the FastConformer ONNX model running on ONNX Runtime Web (WASM). The CTC decoder produces timestamped words, which are matched to the Quranic text using normalized Levenshtein distance.
Package creation keeps the current MP3 byte-for-byte and writes its timing JSON into a two-file ZIP locally. FFmpeg is loaded only when you explicitly apply an audio trim.
The AI model used is open source.GitHub Repo