Gipformer ASR

---

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**: `g-group-ai-lab/gipformer-65M-rnnt` (65M params, int8/fp32 ONNX)

Architecture

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

pip install -r {baseDir}/requirements.txt

System dependency: `ffmpeg` (required for M4A support).

2. Start the server

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

# 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)

# 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.