@@ -10,20 +10,54 @@ Stay tuned for updates and we appreciate your interest in our work. Please conti
## Dependencies
- Python3.8
- Python3.8
- fairseq
- matplotlib
## Repository structure
The repository includes data folders which you need to prepare. The repository also includes example files from the BEA corpus (Hungarian) and the GRASS corpus (Austrian German) which makes it possible to run an example from scratch. The speech data should ne stored in the folder ```BEAGR``` and should look like this:
- BEAGR/data_BEA_CS
- Various speaker (spkID1, spkID2, ...) folders
- Various .wav or .flac files (fs=16kHz)
- BEAGR/data_BEA_RS
- Various speaker (spkID1, spkID2, ...) folders
- Various .wav or .flac files (fs=16kHz)
- BEAGR/data_GR_CS
- Various speaker (spkID1, spkID2, ...) folders
- Various .wav or .flac files (fs=16kHz)
- BEAGR/data_GR_RS
- Various speaker (spkID1, spkID2, ...) folders
- Various .wav or .flac files (fs=16kHz)
As you can see ```BEAGR``` includes the subfolders ```data_BEA_CS``` (BEA Spontaneous Speech), ```data_BEA_RS``` (BEA Read Speech), ```data_GR_CS``` (GRASS Conversational Speech) and ```data_GR_RS``` (GRASS Read Speech). **Please make sure that folders are named like this: ```data_{corpus}_{speakingstyle}```**. The audio files should have a sampling rate of 16kHz and can be .wav or .flac files. Given this structure and after installing/preparing all dependencies (see below) you should be able to run the experiment. To run a specific stage of the script for a specific dataset, provide the directory where all you data is stored (here ```BEAGR```) and an integer as an argument to the `./run.sh` command. For instance, to run stage ```3``` for the example dataset, you would use the following command:
```
./run.sh BEAGR 3
```
The command automatically generates the experiment folder ```exp_BEAGR```. Note that stage ```0``` would run everything in a row.
## Reproduction
The following steps are necessary to reproduce the experiment. At first you need to create a conda envrionment and install the necessary packages. Second you have to clone the fairseq repository and modify the file ```path.sh``` to export necessary environment variables.
### Conda environment
You need to install the following packages:
```
conda env create -f code/environment.yml
conda create -n speechcodebookanalysis python=3.8
conda activate speechcodebookanalysis
pip install fairseq
pip install matplotlib
pip install scikit-learn
pip install faiss-cpu
```
### Fairseq Repository
You need to clone the fairseq repository to another directory (e.g., ```../fairseq```). The file ```path.sh``` needs to modified in order to export the necessary environment variables.
