whisper-large-icelandic-62640-steps-967h-ct2
This is a faster-whisper version of language-and-voice-lab/whisper-large-icelandic-62640-steps-967h.
The model was created like described in faster-whisper:
ct2-transformers-converter --model language-and-voice-lab/whisper-large-icelandic-62640-steps-967h \
--output_dir whisper-large-icelandic-62640-steps-967h-ct2 \
--quantization float16
Usage
from faster_whisper import WhisperModel
model_size = "whisper-large-icelandic-62640-steps-967h-ct2"
# Run on GPU with FP16
model = WhisperModel(model_size, device="cuda", compute_type="float16")
# or run on GPU with INT8
# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
# or run on CPU with INT8
# model = WhisperModel(model_size, device="cpu", compute_type="int8")
segments, info = model.transcribe("audio.mp3", beam_size=5)
print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
for segment in segments:
print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
BibTeX entry and citation info
When publishing results based on these models please refer to:
@inproceedings{mena2024samromur,
title={Samr{\'o}mur Millj{\'o}n: An ASR Corpus of One Million Verified Read Prompts in Icelandic},
author={Mena, Carlos Daniel Hernandez and Gunnarsson, {\TH}orsteinn Da{\dh}i and Gu{\dh}nason, J{\'o}n},
booktitle={Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
pages={14305--14312},
year={2024}
}