The data is used in project https://github.com/Alexander92-cpu/LanguageModel_Fusion
Data desciption:
'asr/stt_en_conformer_transducer_small.nemo' - NeMo ASR pre-trained RNN-T model (https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/stt_en_conformer_transducer_small);
'gpt2' - fine-tuned GPT-2 LM model for rescoring (https://huggingface.co/docs/transformers/model_doc/gpt2#transformers.GPT2LMHeadModel);
'kenlm/4_ngram_output.bin' - 4-gram language model;
'lstm' - trained from scratch word-level LSTM LM model and the corresponding tokenizer;
'text' - contains text data used for training, validation, and testing.
'optimize' - data and results of optimization experiments
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import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("AlexanderMaz/LanguageModel_Fusion") transcriptions = asr_model.transcribe(["file.wav"])