Instructions to use espnet/ta_openslr127 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/ta_openslr127 with ESPnet:
from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "espnet/ta_openslr127" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
| espnet: "202604" | |
| files: | |
| asr_model_file: exp/asr_train_asr_raw_ta_bpe1000_accum_grad1_sp/valid.acc.ave_10best.pth | |
| lm_file: exp/lm_train_lm_ta_bpe1000/valid.loss.ave_1best.pth | |
| python: "3.10.20 (main, Mar 11 2026, 17:46:40) \n[GCC 14.3.0]" | |
| timestamp: 1647958476.960957 | |
| torch: 2.9.1+cu128 | |
| yaml_files: | |
| asr_train_config: exp/asr_train_asr_raw_ta_bpe1000_accum_grad1_sp/config.yaml | |
| lm_train_config: exp/lm_train_lm_ta_bpe1000/config.yaml | |