
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

{"language": ["en"], "license": "apache-2.0", "tags": ["asr", "rescoring", "rnn-t", "gpt2", "nemo", "lstm", "kenlm"], "datasets": ["librispeech_asr"], "metrics": ["wer"], "pipeline_tag": "automatic-speech-recognition"}
nemo asr rescoring rnn-t gpt2 lstm kenlm automatic-speech-recognition en dataset:librispeech_asr license:apache-2.0 region:us