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}
}