• Python 3
• pymystem3: Russian lemmatizer by Yandex https://pypi.org/project/pymystem3/
  pip install pymystem3
• FFMPEG: Command-line tool for audio conversion
  https://ffmpeg.org/download.html
• The OpenRussian dictionary downloaded as a CSV file.
• Specifically, the following files are needed in _materials\openrussian:
  • words.csv
  • translations.csv

Prerequisite:

• A Google service account key for access to the Speech API
  https://console.cloud.google.com/apis/library/speech.googleapis.com
  https://console.cloud.google.com/apis/credentials
  
  • Place ServiceAccountKey.json into solution root
  • Edit values at top of GoogleTranscriber.cs (projectId and bucketName) to match what you set up in API console.

The code in Tool itself takes care of uploading the FLAC file, initiating the transcription, polling for progress, and retrieving the transcribed text.

Prerequisite:

• A subscription key for the speech-to-text service in Azure App Services
  https://portal.azure.com/#blade/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/SpeechServices

How to:

• Transcription is performed by a dedicated tool in the repository, MSTranscriber.
• Use from-mp3.cmd to creat a WAV file with the required parameters. Upload the file to a publicly available URL.
• Create a TranslationConfig.json in the solution root (you can use the sample file). Enter your subscription key, and fill in the URL, language, and output file name
• Build and run MSTranscriber. Working directory must be the solution root.

To prepare, open the Properties of the Tool project in Visual Studio (right-click in Solution Explorer), and under Debug set the solution root as the working directory.

• Convert mp3 file to other formats: Scripts\from-mp3.bat SAMPLE
• Prepare cleaned-up plain text file of text, one line per paragraph. This will live as _work\SAMPLE-orig.txt
• In the Tool project, edit line in Main() to match current conversion: doOrigAlignRus("SAMPLE", (decimal)0.35, "Чехов: Анна на шее");
• Edit the Method doOrigAlignRus for uncomment the return.
• Run the Tool.
• Edit Scripts\rulem.py to work on SAMPLE, and execute: python3 rulem.py
• Edit the Method doOrigAlignRus for comment the return.
• Run the Tool again. Second run skips transcription, and finishes annotation because SAMPLE-lem.txt is now available.

The player is is based on Vue.js; it is currently being built with Node.JS v14. The prerequisites are:

• Node.js v14 (download page)
• Yarn (download page)
• Vue CLI (download page)

• In the ProsePlayer folder, restore Node modules:
  > yarn
• Build the App:
  yarn build

The outcome is in the dist folder, which can be published as-is. Notes:

• Before building, make sure the data for the episodes is in public/media. Alternatively, the same files can be copied directly into dist/media, or the equivalent folder in the published tool online. The pre-processing script copies its outputs into this folder by itself.
• To devolop the tool (run it locally, with livereload), you need:
  yarn serve
• You only need to run yarn again to update the Node modules if the content of package.json has changed.