Update README.md

README.md

@@ -5,12 +5,12 @@ A commonvoice-fi recipe for training ASR engine using Kaldi. The following recip
 
 
 ## Installation
-The author use docker to run the container. **GPU is required** to train `tdnn_chain`, else the script can train only up to `tri3b`.
+Use docker to run the container. **GPU is required** to train `tdnn_chain`, else the script can train only up to `tri3b`.
 
-### Downloading SRILM
+## Downloading SRILM
 Before building docker, SRILM file need to be downloaded. You can download it from [here](http://www.speech.sri.com/projects/srilm/download.html). Once the file is downloaded, remove version name (e.g. from `srilm-1.7.3.tar.gz` to `srilm.tar.gz` and place it inside `docker` directory. Your `docker` directory should contains 2 files: `dockerfile`, and `srilm.tar.gz`.
 
-### Run docker and attach command line
+## Run docker and attach command line
 Since gpu is required you are going to need the kaldi-gpu-image.
 
 ```bash
@@ -21,7 +21,7 @@ Once you finish this step, you should be in a docker container bash shell now
 ## Usage
 To run the training pipeline, go to recipe directory and run `run.sh` script
 ```bash
-$ cd /opt/kaldi/egs/commonvoice-th
+$ cd /opt/kaldi/egs/commonvoice-fi
 $ ./run.sh --stage 0
 ```
 
@@ -31,6 +31,9 @@ Since the dataset is only 14 hours long, it does not contain enough words for th
 
 ## Constructing a working VOSK-model
 
-Vosk is a higher level library that uses Kaldi internally for voice recognition. It requires certain type of Kaldi model in order for it to work.
+Vosk is a higher level library that uses Kaldi internally for voice recognition. It requires certain type of Kaldi-model in order for it to work.
 There is a list in [VOSKs own website](https://alphacephei.com/vosk/models#training-your-own-model) about what the model folder should contain.
-Find these files produced by the scripts and put them in right folders to create a working model. NOTE: take the files from nnet directories. Using files from tri3b or models created by earlier stages won't work.
+Find these files produced by the scripts and put them in right folders to create a working model. NOTE: take the files from `tdnn_chain` directories. Using files from `tri4b` or models created by earlier stages won't work.
+
+## Prebuilt models
+You can download prebuilt models from google drive built with this recipe from [here](https://drive.google.com/drive/folders/1orMXB84d9EXpHrNaI5wlynkvXCOCzwvJ?usp=sharing).