Wav2Vec2 NL A Dutch Wav2Vec2 base model, pre trained on 831 hours of exclusively Dutch speech. Pre training data was extracted from a combination of: the Spoken Dutch Corpus (537 hours; incl. spontaneous conversations, interviews, read speech and news reports) the Dutch component of Multilingual LibriSpeech (211 hours; audiobook segments) the Dutch subset of the CommonVoice 16.1 corpus (83 hours; read aloud speech) More information, incl. the training manifest and configuration is available in the Wav2Vec2 NL repository on Zenodo. Analyses of Dutch phonetic and lexical features encoded in Wav2Vec2 NL hidden states are reported in the paper What do self supervised speech models know about Dutch? Analyzing advantages of language specific pre training (Interspeech 2025; see full citation below). Note: This model does not have a tokenizer as it was pretrained on audio alone. In order to use this model for speech recognition, a tokenizer should be created and the model should be fine tuned on labeled text data. Check out this blog for an explanation of fine tuning Wav2Vec2 models on HuggingFace. Usage Citation The Wav2Vec2 NL model was published as part of: de Heer Kloots, M., Mohebbi,…
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