Wav2Vec2 LJSpeech Gruut Wav2Vec2 LJSpeech Gruut is an automatic speech recognition model based on the wav2vec 2.0 architecture. This model is a fine tuned version of Wav2Vec2 Base on the LJSpech Phonemes dataset. Instead of being trained to predict sequences of words, this model was trained to predict sequence of phonemes, e.g. ["h", "ɛ", "l", "ˈoʊ", "w", "ˈɚ", "l", "d"] . Therefore, the model's vocabulary contains the different IPA phonemes found in gruut. This model was trained using HuggingFace's PyTorch framework. All training was done on a Google Cloud Engine VM with a Tesla A100 GPU. All necessary scripts used for training could be found in the Files and versions tab, as well as the Training metrics logged via Tensorboard. Model Model params Arch. Training/Validation data (text) wav2vec2 ljspeech gruut 94M wav2vec 2.0 LJSpech Phonemes Dataset Evaluation Results The model achieves the following results on evaluation: Dataset PER (w/o stress) CER (w/o stress) : : : : LJSpech Phonemes Test Data 0.99% 0.58% Usage Training procedure Training hyperparameters The following hyperparameters were used during training: learning rate : 0.0001 train batch size : 16 eval batch size : 8 see…
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