Skill: ai-ggroup/gipformer (version 1.0.0)

--- name: gipformer description: Vietnamese speech-to-text using Gipformer ASR (65M params, Zipformer-RNNT). Accepts audio of any length — the server handles VAD chunking, batching, and returns the transcript. Supports WAV, FLAC, OGG, MP3, M4A. Activated when the user provides an audio file (WAV, MP3, M4A, FLAC, OGG) or asks to transcribe/recognize Vietnamese speech, e.g. "transcribe this audio", "nhận dạng giọng nói", "chuyển audio thành text". --- # Gipformer ASR Vietnamese speech recognition — send audio of any length, get transcript. **Huggingface Model**: [REDACTED_SECRET] (65M params, int8/fp32 ONNX) ## Architecture ```mermaid flowchart TD A[Audio file] -->|base64 encode| B[POST /transcribe] B --> C[Decode & resample to 16kHz] C --> D[VAD chunking ≤ 20s] D --> E[Batch inference — sherpa-onnx] E --> F[Merge chunk texts] F --> G["{ transcript, chunks }"] ``` The client sends base64-encoded audio (any length, any format). The server decodes, chunks with VAD, infers in batches, and returns the full transcript. ## Quick Start ### 1. Install dependencies ```bash pip install -r {baseDir}/requirements.txt ``` System dependency: `ffmpeg` (required for M4A support). ### 2. Start the server ```bash python {baseDir}/scripts/serve.py # or with options: python {baseDir}/scripts/serve.py --port 8910 --quantize int8 --max-batch-size 32 ``` The server downloads the ASR model + VAD model on first run and listens on `http://127.0.0.1:8910`. ### 3. Transcribe audio ```bash # Single file (any format) python {baseDir}/scripts/transcribe.py audio.wav python {baseDir}/scripts/transcribe.py recording.mp3 # Multiple files python {baseDir}/scripts/transcribe.py *.wav # JSON output with chunk details python {baseDir}/scripts/transcribe.py audio.wav --json # Save results python {baseDir}/scripts/transcribe.py audio.wav -o results.json ``` ### 4. Direct API call (curl) ```bash # Transcribe (any length, any format) curl -X POST http://127.0.0.1:8910/transcribe \ -H "Content-Type: application/json" \ -d "{\"audio_b64\": \"$(base64 -i audio.wav)\"}" # Response: # { "transcript": "full text...", "duration_s": 120.5, "process_time_s": 5.2, # "chunks": [{"text": "...", "start_s": 0.0, "end_s": 8.7}, ...] } # Health check curl http://127.0.0.1:8910/health ``` ## Audio Format | Format | Extension | Support | |--------|-----------|---------| | WAV | .wav | Native (soundfile) | | FLAC | .flac | Native (soundfile) | | OGG | .ogg | Native (soundfile) | | MP3 | .mp3 | Native (soundfile) | | M4A/AAC | .m4a | Via ffmpeg | All formats are converted to WAV 16-bit PCM mono 16kHz internally. ## Server Tuning | Flag | Default | Effect | |------|---------|--------| | `--quantize` | int8 | `fp32` for accuracy, `int8` for speed/size | | `--max-batch-size` | 16 | Higher = more throughput, more latency | | `--max-wait-ms` | 100 | How long to wait before flushing a partial batch | | `--num-threads` | 4 | ONNX runtime threads | | `--decoding-method` | modified_beam_search | `greedy_search` for faster speed | ## API Reference See [references/api.md](references/api.md) for full endpoint documentation.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)