⚡ Vaani1-Lite-ASR-Turbo (Multilingual)

High-Speed Production Engine by Sorika Labs

CTranslate2 (faster-whisper) format of sorika-labs/vaani1-lite-asr

Vaani1-Lite-ASR-Turbo is the official CTranslate2-optimized release of the Vaani1-Lite-ASR model. It provides 4x-5x faster inference, cuts memory consumption by 50% (only ~484MB), and delivers real-time speech-to-text with latency under 150ms across 99+ languages (Hindi, English, Chinese, Japanese, Korean, Spanish, etc.).

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🌍 Multilingual Capabilities

• Hindi (hi): SOTA fine-tuned accuracy (12.68% WER, beats Whisper-Large-v3).
• English (en): 3.70% WER (Zero catastrophic forgetting).
• East Asian (zh, ja, ko): Full transcription support for Chinese, Japanese, and Korean.
• Indic Languages: Bengali, Tamil, Telugu, Marathi, Gujarati, Urdu, Kannada, Malayalam, Punjabi.
• Auto-Detection: Automatically identifies the spoken language from audio.

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🚀 Quickstart: Real-Time Transcription

Install faster-whisper:

pip install faster-whisper

Transcribe with Python:

from faster_whisper import WhisperModel

# Load the turbo model on CPU (uses ~250MB RAM)
model = WhisperModel("sorika-labs/vaani1-lite-asr-turbo", device="cpu", compute_type="int8")

# Transcribe Hindi, English, Chinese, Korean, or Auto-Detect:
segments, info = model.transcribe("sample_audio.wav", vad_filter=True)

print(f"Detected Language: {info.language} ({info.language_probability:.2f})")
for segment in segments:
    print(f"[{segment.start:.2f}s -> {segment.end:.2f}s] {segment.text}")

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🔗 Models in this Family

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📜 License & Developer

• License: MIT (Permissive open source)
• Developer: Sorika Labs