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burakaydinofficial/whisper-tiny-24lang
whisper-tiny-24lang is a automatic speech recognition model from burakaydinofficial. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
A plain openai/whisper-tiny (unmodified architecture) fine-tuned on the 24 languages of the CC0 Whispered corpus. This is the matched scientific control for burakaydinofficial/whisper-tiny-mla-24lang —
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From the Hugging Face model README
A plain openai/whisper-tiny (unmodified architecture) fine-tuned on the 24 languages of the CC0
Whispered corpus. This is the
matched scientific control for burakaydinofficial/whisper-tiny-mla-24lang —
trained identically, minus the MHA→MLA conversion — published so the MLA conversion cost is
independently reproducible. No custom code: loads directly in transformers, and — being a plain unmodified Whisper — is convertible for faster-whisper / CTranslate2 / whisper.cpp via their standard converters.
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor
model = AutoModelForSpeechSeq2Seq.from_pretrained("burakaydinofficial/whisper-tiny-24lang") # no trust_remote_code
processor = AutoProcessor.from_pretrained("burakaydinofficial/whisper-tiny-24lang")
Evaluate this control and whisper-tiny-mla-24lang on CommonVoice-17 (scripts/validate.py in the
code repo); the per-language difference is the
conversion cost reported on the MLA card and in docs/results/.
Reconstructed numbers. This control's per-language WER/CER in the table are reconstructed as (the MLA model's absolute score − the measured paired conversion cost), not from a separate evaluation of this checkpoint; an independent re-eval may differ by a few tenths. The paired conversion cost is the directly measured quantity.
| Lang | this control |
|---|---|
| en | 28.1 WER |
| de | 42.1 WER |
| es | 29.5 WER |
| fr | 44.8 WER |
| it | 43.8 WER |
| pt | 43.1 WER |
| ru | 40.6 WER |
| nl | 38.8 WER |
| pl | 47.3 WER |
| id | 53.0 WER |
| tr | 52.1 WER |
| hi | 45.9 WER |
| ms | 49.5 WER |
| sv-SE | 57.9 WER |
| th | 32.0 CER |
| zh-CN | 34.7 CER |
| cs | 67.2 WER |
| vi | 54.4 WER |
| fi | 66.9 WER |
| el | 63.7 WER |
| da | 73.7 WER |
| ja | 48.8 CER |
| nn-NO | 93.1 WER |
| ko | 71.3 WER |
Encoder frozen during fine-tuning; 15,000 steps, warmup+cosine, fp16. Read-speech domain (CommonVoice + FLEURS-validated). "Compression cost" does not apply to this unconverted control.