Instructions to use TalTechNLP/icefall_pruned_transducer_stateless7_streaming_et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- K2
How to use TalTechNLP/icefall_pruned_transducer_stateless7_streaming_et with K2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Icefall streaming ASR model for Estonian
This is a streaming end-to-end transducer model for Estonian, trained using Icefall
It is trained on around 800 h of manually transcribed speech from various domains and on about 2500 h of automatically transcribed speech from Estonian TV (mainly news and talkshows)
Serving
To use it on a server for browser-based ASR:
Install Sherpa
Clone this model locally:
git lfs install git clone https://huggingface.co/TalTechNLP/icefall_pruned_transducer_stateless7_streaming_etSet SHERPA_ROOT_DIR to the sherpa root directory
Start serving on port 6006:
sherpa-online-websocket-server --use-gpu=false --decode-chunk-size=32 \ --encoder-model=icefall_pruned_transducer_stateless7_streaming_et/exp/1d/encoder_jit_trace.pt \ --decoder-model=icefall_pruned_transducer_stateless7_streaming_et/exp/1d/decoder_jit_trace.pt \ --joiner-model=icefall_pruned_transducer_stateless7_streaming_et/exp/1d/joiner_jit_trace.pt \ --tokens=icefall_pruned_transducer_stateless7_streaming_et/data/lang_bpe_1000/tokens.txt \ --doc-root=${SHERPA_ROOT_DIR}/sherpa/bin/web --decoding-method=modified_beam_searchOpen in browser: http://localhost:6006 (also works via ssh tunnel) and go to "Streaming-Record" tab
Click "Connect" and then "Streaming-Record" button, and start talking
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