Gettyappz/mums-ears-models

Mum's Ears — ONNX Model Repository

Central model store for Mum's Ears, an Android speech-to-text app built with Flutter and sherpa-onnx.

All models are downloaded at runtime with SHA-256 checksum verification.

---

Folder Structure

mums-ears-models/ ├── en/ # English streaming ASR + punctuation ├── de/ # German streaming ASR ├── es/ # Spanish streaming ASR ├── fr/ # French streaming ASR ├── zh/ # Chinese streaming ASR ├── qwen3-asr/ # Qwen3-ASR (offline, 938 MB) ├── audio_tagging/ # CED Tiny audio event classification ├── denoiser/ # DPDFNet8 speech enhancement ├── speaker_embedder/ # CAM++ speaker embedding └── pyannote_model.onnx # Speaker diarization segmentation

---

Model Inventory

Streaming ASR (per-language)

Each language folder contains a streaming Zipformer transducer model fine-tuned for real-time captioning.

File	Size	Purpose
encoder.onnx	70 MB (154 MB zh)	Acoustic encoder
decoder.onnx	1 MB (5 MB zh)	Prediction decoder
joiner.onnx	1 MB	Joint network
tokens.txt	< 1 MB	Token vocabulary

Languages: en, de, es, fr, zh

Punctuation (English)

File	Size	Purpose
en/model_punct.int8.onnx	7 MB	Online punctuation model (int8 quantized)
en/bpe_punct.vocab	< 1 MB	BPE vocabulary

Speaker Diarization

File	Size	Purpose	Original Source
pyannote_model.onnx	14 MB	Speaker segmentation (pyannote 3.0)	csukuangfj/sherpa-onnx-pyannote-segmentation-3-0
speaker_embedder/<filename>	27 MB	CAM++ speaker embeddings (zh+en, 192-dim)	k2-fsa/sherpa-onnx

Audio Tagging

File	Size	Purpose	Original Source
audio_tagging/model.int8.onnx	27 MB	CED Tiny audio event classifier (int8)	k2-fsa/sherpa-onnx-ced-tiny-audio-tagging-2024-04-19
audio_tagging/class_labels_indices.csv	< 1 MB	Audio event class labels	Same

Speech Enhancement (Denoiser)

File	Size	Purpose	Original Source
denoiser/dpdfnet8.onnx	14 MB	DPDFNet8 speech denoiser	k2-fsa/sherpa-onnx

Qwen3-ASR (Offline)

Large offline ASR model (int4 quantized, ~938 MB total). Optional — requires ≥ 4 GB free RAM.

File	Size	Purpose
qwen3-asr/encoder.int8.onnx	~400 MB	Audio encoder
qwen3-asr/decoder.int8.onnx	~400 MB	Language model decoder
qwen3-asr/conv_frontend.onnx	~100 MB	Convolutional frontend
qwen3-asr/tokenizer/vocab.json	< 1 MB	Tokenizer vocabulary
qwen3-asr/tokenizer/merges.txt	< 1 MB	BPE merge rules
qwen3-asr/tokenizer/tokenizer_config.json	< 1 MB	Tokenizer config

---

Attribution

Models in this repository are sourced from the following open-source projects:

• k2-fsa/sherpa-onnx — Streaming ASR, speaker embedding, diarization, punctuation, denoiser, audio tagging (Apache-2.0)
• pyannote/segmentation-3.0 — Speaker diarization segmentation (MIT)
• Qwen/Qwen3-ASR — Offline ASR model (Apache-2.0)
• frankyoujian/Edge-Punct-Casing — Punctuation model (paper)

The "kroko" streaming ASR models (en/de/es/fr) are custom fine-tuned variants. The Chinese streaming model is int8-quantized.

---

Download & Verification

Models are downloaded by the app's built-in download manager with:

• Resumable downloads via HTTP Range headers (.part files)
• SHA-256 checksum verification before accepting any file
• Mirror fallback — if the primary URL fails, the original source URL is tried automatically
• WiFi-only mode (default, toggleable)

All checksums are defined in lib/services/model_checksums.dart.