---
license: apache-2.0
pipeline_tag: automatic-speech-recognition
language:
- en
tags:
- audio
- asr
- ensemble
- orze
datasets:
- hf-audio/open-asr-leaderboard
---

# Orze-ASR-3Way

Orze-ASR-3Way is a deterministic English ASR consensus system selected by Orze
for the Open ASR Leaderboard. It uses
[`bosonai/Qwen3-ASR-1.7B-hf-orze`](https://huggingface.co/bosonai/Qwen3-ASR-1.7B-hf-orze)
as its anchor and two independent voters:
[`HojoAI/Hojo-ASR-V1`](https://huggingface.co/HojoAI/Hojo-ASR-V1) and
[`OpenMOSS-Team/MOSS-Transcribe-preview-2B`](https://huggingface.co/OpenMOSS-Team/MOSS-Transcribe-preview-2B).

The anchor transcript is retained unless both voters agree on the same aligned
word edit. A substitution or deletion is accepted only when both voters agree;
an insertion is accepted only when both voters produce the same insertion at
the same anchor boundary. The official English normalizer is applied before
word alignment. The same rule and decoding parameters are used on every
dataset.

## Immutable components

| Role | Checkpoint | Revision |
|---|---|---|
| Anchor | `bosonai/Qwen3-ASR-1.7B-hf-orze` | `bce834cee3d106a9f0ec1ba98e96d995f13f59de` |
| Voter 1 | `HojoAI/Hojo-ASR-V1` | `a22c381896ce5f4b70038982bfb888fe9969ed99` |
| Voter 2 | `OpenMOSS-Team/MOSS-Transcribe-preview-2B` | `c4b3988677df13c14e79d9db59f356ed761db366` |

The reproducible Docker evaluator is hosted at
[`erik-at-boson/open-asr-leaderboard-orze-ensemble`](https://huggingface.co/spaces/erik-at-boson/open-asr-leaderboard-orze-ensemble).
It runs the checkpoints sequentially and includes the sum of all three inference
times in RTFx.

## Open ASR Leaderboard results

These results use the official evaluator and normalizer at commit
`d1e99b25524814332d6868a5645e568670834cfb`.

| Dataset | WER (%) |
|---|---:|
| AMI Cleaned | 6.93 |
| Earnings22 Cleaned AA (chunked) | 5.24 |
| GigaSpeech Cleaned | 6.68 |
| LibriSpeech test-clean | 1.02 |
| LibriSpeech test-other | 2.41 |
| SPGISpeech | 1.58 |
| VoxPopuli Cleaned AA | 2.78 |
| **Mean** | **3.81** |

Measured aggregate model throughput is **29.66 RTFx**, calculated from the sum
of all three component inference times. The reproducible evaluator also records
the small consensus-alignment overhead when it generates fresh manifests.

## Held-out conversational proxy

The same fixed consensus rule was evaluated on three disjoint deterministic
selections of 200 segments from the evaluation-only AppTek multi-accent
call-center corpus. These selections were not used for training. Lower WER is
better.

| Selection | Anchor overall | Consensus overall | Anchor accent macro | Consensus accent macro |
|---|---:|---:|---:|---:|
| 1 | 10.23 | 9.88 | 11.274 | 10.786 |
| 2 | 7.24 | 6.99 | 7.024 | 6.762 |
| 3 | 9.46 | 9.15 | 9.216 | 8.954 |

Both individual voters were worse than the anchor on all three selections; the
unanimity gate nevertheless improved the anchor consistently. No private Open
ASR Leaderboard data was accessed.

The fixed rule was also checked on a deterministic, balanced 300-utterance
MInDS-14 holdout spanning `en-AU`, `en-GB`, and `en-US`. Overall WER improved
from **31.24** to **31.04**, and locale-macro WER improved from **31.32** to
**31.13**. The consensus changed 87 normalized transcripts: 38 improved, 34
worsened, and 15 were error-neutral, for 10 fewer word errors in aggregate.
Hojo and MOSS individually scored 52.37 and 39.18 WER on the same selection.

## Scope and limitations

This is a 9.64B-parameter composite system (2.04B Orze Qwen, 5.18B Hojo, and 2.42B
MOSS) optimized for English short-form ASR. It trades throughput and memory
footprint for accuracy. The models run sequentially, so peak inference memory
is the maximum of the components rather than their sum. See each component card
for its training disclosure and limitations; the Orze anchor card contains the
fine-tuning disclosure for the only checkpoint trained as part of this work.

## License

The consensus code and all three component checkpoints are Apache-2.0.