File size: 1,801 Bytes
37e3576 12ebabf 37e3576 4131987 6d99fe6 4131987 6d99fe6 4131987 6d99fe6 4131987 6d99fe6 4131987 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 |
---
language:
- et
library_name: k2
tags:
- automatic-speech-recognition
- k2
widget:
- example_title: AK test 1
src: >-
https://huggingface.co/TalTechNLP/icefall_pruned_transducer_stateless7_streaming_et/resolve/main/test_wav.wav
license: cc-by-sa-4.0
---
# Icefall streaming ASR model for Estonian
This is a streaming end-to-end transducer model for Estonian, trained using [Icefall](https://github.com/k2-fsa/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](https://github.com/k2-fsa/sherpa)
* Clone this model locally:
```
git lfs install
git clone https://huggingface.co/TalTechNLP/icefall_pruned_transducer_stateless7_streaming_et
```
* Set 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_search
```
* Open 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
|