Model Card for MultiBridge/wav2vec LnNor IPA ft This model is built for phoneme recognition tasks. It was developed by fine tuning the wav2vec2 base model on TIMIT and LnNor datasets. The predictions are in IPA. Model Details Model Description Developed by: Multibridge Funded by [optional]: EEA Financial Mechanism and Norwegian Financial Mechanism Shared by [optional]: Multibridge Model type: Transformer Language(s) (NLP): English License: cc by 4.0 Finetuned from model [optional]: facebook/wav2vec2 base Uses Automatic phonetic transcription: Converting raw speech into phoneme sequences. Speech processing applications: Serving as a component in speech processing pipelines or prototyping. Bias, Risks, and Limitations data specificity: By excluding recordings shorter than 2 seconds or longer than 30 seconds, and labels with fewer than 5 phonemes, some natural speech variations are ignored. This might affect the model's performance in real world applications. The model's performance is influenced by the characteristics of TIMIT and LnNor datasets. This can lead to potential biases, especially if the target application involves speakers or dialects not well represented in these dataset…
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