g-group-ai-lab/gipformer-65M-rnnt

Model

Gipformer - Efficient Vietnamese Speech Recognition

26

12 commits

2 linked in READMEs

updated Sep 17, 2026

See the code

README

Gipformer - Efficient Vietnamese Speech Recognition

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.
  • 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.
  • gipformer-68M-rnnt is based on Zipformer Transducer architecture.

Benchmark Results

We evaluate gipformer-68M-rnnt against 12 established Vietnamese ASR models across 12 benchmarks spanning call center, medical, broadcast, read speech, etc. All numbers are Word Error Rate (WER %) β€” lower is better.

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

ModelParamstele-mediumtele-diff-northtele-diff-middletele-diff-southMultiMEDVietMedvlsp-t1vlsp-t2LSVSCFleursViMDvivos
vinai/PhoWhisper-small244M33.9655.8865.4162.3526.0225.5015.9934.2011.2316.1114.096.23
vinai/PhoWhisper-medium769M26.4651.2059.0455.3924.7624.9014.0626.3810.2514.4411.344.93
vinai/PhoWhisper-large1.5B26.8250.3959.4456.7024.4724.3713.7027.4510.0812.6211.184.73
khanhld/chunkformer-large-vie110M27.6046.3051.9149.0922.6019.5914.0925.818.8514.1711.774.18
nguyenvulebinh/wav2vec2-base-vi95M23.7140.4948.9046.3323.0322.9613.1437.339.8920.0911.426.60
hynt/Zipformer-30M-RNNT-6000h30M19.9538.7745.1943.8919.8519.9311.7628.639.1213.167.284.60
VietASR-zipformer68M20.3042.2149.0147.8622.0521.9014.5431.1810.2314.7610.156.92
Qwen/Qwen3-ASR-1.7B1.7B26.3446.8059.8551.8420.1120.2116.2934.269.6410.1311.167.17
Qwen/Qwen3-ASR-0.6B600M32.2948.5761.8855.4322.6522.5118.6243.4410.9613.1114.3710.23
nvidia/parakeet-ctc-0.6b-Vietnamese600M31.8255.3361.6556.7023.7923.5317.0037.9410.4616.1112.957.76
g-group-ai-lab/gipformer-68M-rnnt68M15.5325.1032.2732.6219.3519.4113.3920.408.9612.927.174.12

Rankings Summary

RankCountBenchmarks
#19 / 12tele-medium, tele-difficult-north, tele-difficult-middle, tele-difficult-south, MultiMED, VietMed, vlsp-2020-task-2, ViMD, vivos
#21 / 12LSVSC (8.96)
#32 / 12vlsp-2020-task-1 (13.39), Fleurs (12.92)
Dataset Descriptions

Private test sets (call center domain):

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

Public test sets:

  • MultiMED β€” Multi-domain medical conversations
  • VietMed β€” Vietnamese medical domain
  • vlsp-2020-task-1 β€” VLSP 2020 ASR Shared Task 1
  • vlsp-2020-task-2 β€” VLSP 2020 ASR Shared Task 2
  • 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
  • vivos β€” Vietnamese read speech corpus

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. gipformer-68M-rnnt delivers dominant performance across all call center test sets.

Resources

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/gipformer-68M-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.

automatic-speech-recognition
edge-ai
edge-device
gipformer
int8
onnx
onnxruntime
quantized
rnnt
rnn-transducer
speech-to-text
vietnamese
zipformer
zipformer-transducer

g-group-ai-lab/gipformer-65M-rnnt

Model

Gipformer - Efficient Vietnamese Speech Recognition

26

12 commits

2 linked in READMEs

updated Sep 17, 2026

See the code

README

Gipformer - Efficient Vietnamese Speech Recognition

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.
  • 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.
  • gipformer-68M-rnnt is based on Zipformer Transducer architecture.

Benchmark Results

We evaluate gipformer-68M-rnnt against 12 established Vietnamese ASR models across 12 benchmarks spanning call center, medical, broadcast, read speech, etc. All numbers are Word Error Rate (WER %) β€” lower is better.

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

ModelParamstele-mediumtele-diff-northtele-diff-middletele-diff-southMultiMEDVietMedvlsp-t1vlsp-t2LSVSCFleursViMDvivos
vinai/PhoWhisper-small244M33.9655.8865.4162.3526.0225.5015.9934.2011.2316.1114.096.23
vinai/PhoWhisper-medium769M26.4651.2059.0455.3924.7624.9014.0626.3810.2514.4411.344.93
vinai/PhoWhisper-large1.5B26.8250.3959.4456.7024.4724.3713.7027.4510.0812.6211.184.73
khanhld/chunkformer-large-vie110M27.6046.3051.9149.0922.6019.5914.0925.818.8514.1711.774.18
nguyenvulebinh/wav2vec2-base-vi95M23.7140.4948.9046.3323.0322.9613.1437.339.8920.0911.426.60
hynt/Zipformer-30M-RNNT-6000h30M19.9538.7745.1943.8919.8519.9311.7628.639.1213.167.284.60
VietASR-zipformer68M20.3042.2149.0147.8622.0521.9014.5431.1810.2314.7610.156.92
Qwen/Qwen3-ASR-1.7B1.7B26.3446.8059.8551.8420.1120.2116.2934.269.6410.1311.167.17
Qwen/Qwen3-ASR-0.6B600M32.2948.5761.8855.4322.6522.5118.6243.4410.9613.1114.3710.23
nvidia/parakeet-ctc-0.6b-Vietnamese600M31.8255.3361.6556.7023.7923.5317.0037.9410.4616.1112.957.76
g-group-ai-lab/gipformer-68M-rnnt68M15.5325.1032.2732.6219.3519.4113.3920.408.9612.927.174.12

Rankings Summary

RankCountBenchmarks
#19 / 12tele-medium, tele-difficult-north, tele-difficult-middle, tele-difficult-south, MultiMED, VietMed, vlsp-2020-task-2, ViMD, vivos
#21 / 12LSVSC (8.96)
#32 / 12vlsp-2020-task-1 (13.39), Fleurs (12.92)
Dataset Descriptions

Private test sets (call center domain):

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

Public test sets:

  • MultiMED β€” Multi-domain medical conversations
  • VietMed β€” Vietnamese medical domain
  • vlsp-2020-task-1 β€” VLSP 2020 ASR Shared Task 1
  • vlsp-2020-task-2 β€” VLSP 2020 ASR Shared Task 2
  • 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
  • vivos β€” Vietnamese read speech corpus

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. gipformer-68M-rnnt delivers dominant performance across all call center test sets.

Resources

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/gipformer-68M-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.

automatic-speech-recognition
edge-ai
edge-device
gipformer
int8
onnx
onnxruntime
quantized
rnnt
rnn-transducer
speech-to-text
vietnamese
zipformer
zipformer-transducer