wav2vec2 xls r parlaspeech hr This model for Croatian ASR is based on the facebook/wav2vec2 xls r 300m model and was fine tuned with 300 hours of recordings and transcripts from the ASR Croatian parliament dataset ParlaSpeech HR v1.0. Notice: ParlaSpeech corpora are currently in the process of enrichment with new features. Follow our progress here: http://clarinsi.github.io/parlaspeech If you use this model, please cite the following paper: Nikola Ljubešić, Danijel Koržinek, Peter Rupnik, Ivo Pavao Jazbec. ParlaSpeech HR a freely available ASR dataset for Croatian bootstrapped from the ParlaMint corpus. http://www.lrec conf.org/proceedings/lrec2022/workshops/ParlaCLARINIII/pdf/2022.parlaclariniii 1.16.pdf Metrics Evaluation is performed on the dev and test portions of the ParlaSpeech HR v1.0 dataset. split CER WER dev 0.0335 0.1046 test 0.0234 0.0761 There are multiple models available, and in terms of CER and WER, the best performing model is wav2vec2 large slavic parlaspeech hr lm. Usage in transformers Training hyperparameters In fine tuning, the following arguments were used: arg value per device train batch size 16 gradient accumulation steps 4 num train epochs 8 learning rate…
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