Update Model Card with mobile Sherpa-ONNX specs

667748c verified 20 days ago

2.67 kB

license: mit
language:
  - hi
  - bn
  - te
  - ta
  - mr
  - gu
  - kn
  - ml
  - pa
  - or
  - as
  - ur
  - sa
  - ne
  - kok
  - mai
  - brx
  - doi
  - ks
  - mni
  - sat
  - sd
  - en
tags:
  - audio
  - automatic-speech-recognition
  - speech-to-text
  - onnx
  - int8
  - sherpa-onnx
  - indicconformer
  - ai4bharat
  - mobile-edge
pipeline_tag: automatic-speech-recognition

🎙️ BharatBhasha AI - Speech Recognition (STT) Models

Production-grade, INT8-quantized acoustic models based on AI4Bharat IndicConformer for real-time offline speech transcription in 22 Indian scheduled languages + English.

📦 Model Artifacts & Architecture

Language	Model File	Vocabulary File	Size	Format
Telugu (`te`)	`indic_conformer_te.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Hindi (`hi`)	`indic_conformer_hi.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Tamil (`ta`)	`indic_conformer_ta.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Kannada (`kn`)	`indic_conformer_kn.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Bengali (`bn`)	`indic_conformer_bn.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Marathi (`mr`)	`indic_conformer_mr.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Gujarati (`gu`)	`indic_conformer_gu.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Malayalam (`ml`)	`indic_conformer_ml.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Punjabi (`pa`)	`indic_conformer_pa.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
Odia (`or`)	`indic_conformer_or.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX
English (`en`)	`indic_conformer_en.onnx`	`tokens_en.txt`	188 MB	NeMo CTC INT8 ONNX
All other Indian Langs	`indic_conformer_<lang>.onnx`	`tokens.txt`	188 MB	NeMo CTC INT8 ONNX

📱 Mobile Android Deployment (Sherpa-ONNX)

Add to build.gradle.kts:

dependencies {
    implementation("com.k2fsa.sherpa.onnx:sherpa-onnx:1.10.30")
}

Initialize offline recognizer:

val config = OfflineRecognizerConfig(
    featConfig = FeatureConfig(sampleRate = 16000, featureDim = 80),
    modelConfig = OfflineModelConfig(
        nemoCtc = OfflineNemoEncDecCtcModelConfig(model = modelPath),
        tokens = tokensPath,
        numThreads = 2,
        debug = false
    )
)
val recognizer = OfflineRecognizer(config)

⚡ Performance Highlights

100% Offline: Zero internet connection or Google speech services required.
Native Script Output: Emits authentic Unicode characters (Telugu script, Devanagari, Bengali, Tamil, etc.).
Latency: Real-Time Factor (RTF) < 0.25 on standard Android mobile processors.