Gipformer 1.5 - Efficient Vietnamese Speech Recognition

Source code: github.com/ggroup-ai-lab/gipformer

Demo: Try gipformer in your browser

Highlights

  • State-of-the-art accuracy β€” Demonstrates top-tier performance across major Vietnamese ASR benchmarks, delivering highly precise and reliable transcription quality.
  • Robust handling of telephonic domains β€” Excels in processing challenging, noisy real-world call center recordings across all major Vietnamese regional accents.
  • Domain-leading accuracy β€” Best WER on the technology, finance, education, public administration and medical benchmarks.
  • Outstanding parameter efficiency β€” Ranks among the smallest ASR models currently available.
  • Seamless edge deployment β€” Its naturally low resource requirements enable ultra-fast inference on mobile and embedded systems, making it perfectly suited for offline, on-device applications.
  • Built-in data privacy β€” By supporting full local execution, the model ensures sensitive audio data is processed securely on-device, eliminating the need for third-party cloud services.
  • gipformer1.5-65M-rnnt is based on the Zipformer Transducer architecture.

Benchmark Results (WER%)

Lower is better; bold = best in each column.

Normalization: Both predictions and labels are normalized before computing WER β€” lowercased, diacritics removed, and numbers converted to spoken form.

Model Params tele-medium tele-hard-north tele-hard-middle tele-hard-south vi-asr-tech vi-asr-edu vi-asr-finance vi-asr-pubadmin vivos Common-Voice vlsp-t1 VietMed MultiMED LSVSC Fleurs ViMD
vinai/PhoWhisper-small 244M 33.96 55.88 65.41 62.35 56.81 51.87 47.36 41.46 6.23 11.55 15.99 25.50 26.02 11.23 16.11 14.09
vinai/PhoWhisper-medium 769M 26.46 51.20 59.04 55.39 47.93 43.00 41.60 34.81 4.93 8.37 14.06 24.90 24.76 10.25 14.44 11.34
vinai/PhoWhisper-large 1.5B 26.82 50.39 59.44 56.70 42.94 44.99 40.54 33.78 4.73 8.60 13.70 24.37 24.47 10.08 12.62 11.18
Qualcomm-AI-Research/PhoASR-whisper-small 244M 30.73 50.30 56.66 54.12 44.35 41.65 β€” 35.99 5.87 9.73 14.60 23.10 22.78 7.59 13.97 9.75
nvidia/parakeet-ctc-0.6b-Vietnamese 600M 31.82 55.33 61.65 56.70 48.69 45.86 43.16 38.84 7.76 11.40 17.00 23.53 23.79 10.46 16.11 12.95
khanhld/chunkformer-large-vie 110M 27.60 46.30 51.91 49.09 39.81 37.20 34.31 29.30 4.18 6.94 14.09 19.59 22.60 8.85 14.17 11.77
nguyenvulebinh/wav2vec2-base-vi 95M 23.71 40.49 48.90 46.33 59.86 53.06 49.66 39.82 6.60 12.61 13.14 22.96 23.03 9.89 20.09 11.42
zipformer-rnnt 65M 20.30 42.21 49.01 47.86 36.81 30.26 29.13 18.62 6.92 11.48 14.54 21.90 22.05 10.23 14.76 10.15
Qwen/Qwen3-ASR-1.7B 1.7B 26.34 46.80 59.85 51.84 27.95 29.93 34.09 31.83 7.17 10.76 16.29 20.21 20.11 9.64 10.13 11.16
Qwen/Qwen3-ASR-0.6B 600M 32.29 48.57 61.88 55.43 37.52 36.97 38.31 38.65 10.23 16.68 18.62 22.51 22.65 10.96 13.11 14.37
hynt/Zipformer-30M-RNNT-6000h 30M 19.53 38.13 44.73 41.58 29.77 25.91 25.86 17.92 4.55 4.16 11.78 19.91 19.88 9.04 13.03 7.18
g-group-ai-lab/gipformer-65M-rnnt 65M 15.53 25.10 32.27 32.62 36.59 29.81 29.67 20.09 4.12 6.63 13.39 19.41 19.35 8.96 12.92 7.17
g-group-ai-lab/gipformer1.5-65M-rnnt 65M 15.44 26.24 33.31 32.48 27.49 23.32 22.34 14.82 4.25 6.45 13.37 19.23 19.17 8.97 12.65 7.00

Dataset Descriptions

Private test sets (call center domain):

  • tele-medium β€” Call center recordings with medium difficulty
  • tele-hard-north β€” Low-quality call center audio, hard-to-hear speakers β€” Northern Vietnamese accent
  • tele-hard-middle β€” Low-quality call center audio, hard-to-hear speakers β€” Central Vietnamese accent
  • tele-hard-south β€” Low-quality call center audio, hard-to-hear speakers β€” Southern Vietnamese accent

Public test sets:

  • vi-asr-tech-test β€” Technology: consumer electronics reviews, software tutorials, programming and IT walkthroughs
  • vi-asr-edu-test β€” Education: study-abroad consulting, exam guidance, university and training-course introductions
  • vi-asr-finance-test β€” Finance: stock market commentary, trading platforms, banking and crypto
  • vi-asr-pubadmin-test β€” Public administration: administrative procedures, licensing guidance, civil records
  • vivos β€” Vietnamese read speech corpus
  • Common-Voice β€” Mozilla Common Voice, Vietnamese subset
  • vlsp-t1 β€” VLSP 2020 ASR Shared Task 1
  • VietMed β€” Vietnamese medical domain
  • MultiMED β€” Multi-domain medical conversations
  • LSVSC β€” Large-Scale Vietnamese Speech Corpus
  • Fleurs β€” Google's Few-shot Learning Evaluation of Universal Representations of Speech, Vietnamese subset
  • ViMD β€” Vietnamese Multi-Domain

Call Center Domain: Where It Matters Most

Call center ASR is one of the most challenging real-world domains β€” noisy phone lines, overlapping speech, diverse regional accents, and spontaneous conversation. The gipformer family holds the best result on all four call center test sets, and no other model comes within 9 WER points on any of the three hard subsets.

Usage

See the Quick Start guide for detailed usage instructions.

Citation

@misc{gipformer,
  title={Gipformer - Efficient Vietnamese Speech Recognition},
  author={G-Group AI Lab},
  year={2026},
  url={https://huggingface.co/g-group-ai-lab/gipformer1.5-65M-rnnt}
}

License

This model is released under the MIT License.

Acknowledgments

Developed by G-Group AI Lab. For questions, issues, or collaboration inquiries, please visit our HuggingFace organization page.

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