Vezilka Moonshine Base (Macedonian)

Full fine-tune of UsefulSensors/moonshine-base (61.5M parameters) for Macedonian speech recognition, peak learning rate 5e-4 (checkpoint at step 244,000 of a planned 284,226).

Evaluation

Vezilka FINKI Lecture ASR Benchmark (the finki-benchmark configuration of vezilka-ai/macedonian-speech) - five held-out FINKI computer-science lectures with manually reviewed references; neither their audio nor their transcripts were used in training. Normalised WER/CER in % (NFC, lower-cased, punctuation removed); CUDA, float32, batch 1, beam 4.

Usage

from transformers import pipeline

asr = pipeline("automatic-speech-recognition", model="vezilka-ai/vezilka-moonshine-base-mk")
print(asr("speech.wav", generate_kwargs={"max_new_tokens": 192})["text"])

Moonshine reads the raw 16 kHz waveform, so its cost scales with the clip length; its decoder has 194 positions, so keep generations at or below 192 tokens.

Training data

Full fine-tune for 3 epochs (1 % warm-up) on the project's training mix: the Vezilka-ASRI collection export (FINKI lectures, parliamentary sessions and NSSRM audiobooks, automatic transcripts), accepted Doniraj donations (submissions-20260831), the project's YouTube/TV transcript sets (videa_so_transkript_od_yt, alfa_audios, sitel_audios), a jargon set, and the Macedonian subsets of Mozilla Common Voice (CC0-1.0) and Google FLEURS (CC-BY-4.0).

License

Apache-2.0. The base model UsefulSensors/moonshine-base is released under the MIT license.

Acknowledgements

Supported by the Ministry of Education and Science of the Republic of North Macedonia (project "Utilizing AI and National Large Language Models to Advance Macedonian Language Capabilities") and co-funded by the EC/EuroHPC JU, the Ministry of Digital Transformation of the Republic of North Macedonia and the Faculty of Computer Science and Engineering (FINKI), Ss. Cyril and Methodius University in Skopje, through the VEZILKA project, Grant Agreement No. 101263128.

Citation

The data article describing this collection (Gajdov, Karamachoski, Stojcheva, Mishkovski and Mishev, Curated Macedonian speech datasets with regional transcription layers and a manually reviewed FINKI lecture benchmark) is under review; its citation will be added here on publication.