🧠 OtosakuStreamingASR-iOS

OtosakuStreamingASR is a lightweight on-device streaming speech recognition engine for iOS. It performs real-time audio processing using a Conformer-based architecture and CTC decoding.

🚀 Features

• ✅ Fully offline
• 🎙 Real-time streaming speech recognition
• 🛠 Modular architecture (feature extractor, encoder, decoder)

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🎥 Demo

Watch the model running live on iPhone 13:

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📆 Installation

Add the Swift Package to your Xcode project:

https://github.com/Otosaku/OtosakuStreamingASR-iOS

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🧰 Usage Example

import OtosakuStreamingASR
                                                                                                
let asr = OtosakuStreamingASR()

try asr.prepareModel(from: modelURL)

asr.subscribe { text in
    print("🗣 Recognized: \(text)")
}

// Raw audio chunk: [Double] in range [-1.0, 1.0], strictly 2559 samples per chunk (80ms at 16kHz)
try asr.predictChunk(rawChunk: yourRawAudioChunk)

try asr.stop() // Finalize and decode remaining buffer

asr.reset() // Reset internal model state

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🧠 Model Details

• Architecture: Fast Conformer (Cache-Aware Streaming)

• Language: 🇷🇺 Russian (fine-tuned from English)

• Training: 250 hours of Russian speech (30 epochs)

• WER (Word Error Rate):

  • Russian (fine-tuned): 11%
  • English (before fine-tuning): 6.5% on LibriSpeech test-other

🔗 Download Russian model: Link to model

For other languages or custom domains, contact me:

📧 otosaku.dsp@gmail.com

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🧵 OtosakuStreamingASR API

Method	Description
prepareModel(from:)	Load model from directory
predictChunk(rawChunk:)	Submit audio frame ([Double])
stop()	Finalize and decode remaining buffer
reset()	Reset model state
subscribe { String in }	Receive transcribed text in real time

⚠️ Input audio must be sampled at 16kHz and normalized to [-1.0, 1.0], strictly 2559 samples per chunk (80ms at 16kHz)

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🔒 Privacy First

This package is designed with privacy in mind:

• Runs entirely on-device
• No cloud calls or external dependencies

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📩 Contact

If you have any questions, suggestions, or are interested in adapting the model to another language or domain:

Email: otosaku.dsp@gmail.com

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📄 License

MIT License