luweigen/vibevoice-asr-streaming-android

VibeVoice-ASR-Streaming-1.5B — models prepared for Android

Derived from microsoft/VibeVoice-ASR-Streaming-1.5B (MIT) for the native Android app in the vibevoice-android project. Files are downloaded by the app and checked against sha256 values compiled into the APK. See the original model card for intended use, limitations and the license.

File	What	Runs on
encoder.ns_ctx.onnx + encoder.ns_ctx_qnn.bin	Speech encoder (acoustic + semantic tokenizer encoders and connectors), audio[1,83200] → feats[1,26,1536], fp16, QNN HTP context binary compiled offline with onnxruntime-qnn 2.7.0 (QNN 2.51). RMSNorm inputs are pre-scaled by powers of two (eps scaled to match) so that fp16 on the HTP does not flush eps to zero	Snapdragon 8 Elite (SM8750, HTP v79) only; device needs qnn-runtime ≥ 2.51
encoder.static.onnx + encoder.static.onnx.data	The same encoder, fp32, static shapes, FFN as 1×1 convolutions	Any device, ONNX Runtime CPU EP
lm-q4_0.gguf	The Qwen2-1.5B language model as GGUF (Q4_0), Qwen2 BPE tokenizer included. The token embedding table is the model's own; no other changes	llama.cpp (CPU, OpenCL, Hexagon)
special_embeds.bin	float32 [2, 1536]: embeddings of the speech start / end tokens that wrap each chunk's audio features	—

The acoustic latent uses the mean of the VAE posterior (no sampling), which matches the official sampling mode in WER (docs/models.md of the project). Streaming protocol: every 2.93 s of audio (window 3.47 s incl. lookahead), prefill [speech_start, 26 features, speech_end], decode greedily to <|text_chunk_end|>, feed it back; the KV cache is kept across chunks.