https://github.com/ptytb/ritmom

Convert Google Translate Phrasebook to audio tracks
https://github.com/ptytb/ritmom

audio dictionary foreign-language learning translate tts

Last synced: 27 days ago
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Convert Google Translate Phrasebook to audio tracks

• Host: GitHub
• URL: https://github.com/ptytb/ritmom
• Owner: ptytb
• Created: 2018-01-05T17:40:05.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2018-06-26T18:22:08.000Z (over 6 years ago)
• Last Synced: 2024-11-08T10:51:54.407Z (3 months ago)
• Topics: audio, dictionary, foreign-language, learning, translate, tts
• Language: Python
• Size: 551 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
RITMOM - Repetition is the mother of memory.

### What this app does

It's for learning languages. Creates audio tracks from:

- Your **Google Translate favorites** list. Feeds word and phrase pairs from.

- Plain text file with foreign word list. Offline dictionaries are used for translation (WordNet, GoldenDict, Lingoes).

The idea is to use a sequence

- foreign female slow

- native female normal

- example usage phrase female

- foreign male slow

- native female normal

- example usage phrase male

for better memorization.

### What it does not

Text to speech out of a box. It uses 3rd party TTS engines via Windows COM. You have to use

some proprietary TTS engine to generate a good quality narration.

## Usage

1. Install TTS engines

2. You will need *ffmpeg* executable in your PATH to convert your tracks to MP3.

3. Save phrases to `phrases/` dir, both *csv* or *xls* will fit:

![](doc/howto-google-translate.png)

4. `pip install -r requirements.txt`

5. Edit *config.json* file.

**foreign** and **native** parameters must contain substring of description, which can be listed

with this command: `python main.py -l`

Download desired text corpuses to be able to generate context usage phrases.

Corpuses are listed in a `phraseExamples` configuration option:

`import nltk; nltk.download()`

6. Generate audio `python main.py` 

#### Japanese support

For furigana support you'll need [MeCab](https://doc-0s-9o-docs.googleusercontent.com/docs/securesc/bfpns3k4jmfq4rerbchsjt9tvab2g2to/s1rba84ju4ebrtpunekt5uqhrcss5uuo/1518775200000/13553212398903315502/07793478864651846602/0B4y35FiV1wh7WElGUGt6ejlpVXc?e=download&nonce=vrph5sdvr9aks&user=07793478864651846602&hash=km3beiek9q72uomsoljre155mj7m4kkk) executable accessible in your PATH.

You'll need to install the requirements `pip install -r requirements-jp.txt`

#### Offline dictionaries

Supported dictionary formats:

- DSL (Used by [GoldenDict](https://goldendict.org/))

- LDX (Used by [ABBYY Lingvo]() and [Lingoes](https://www.lingoes.net))

- WordNet (through NLTK)

## TODO

- [ ] Fix TidyUpText filter

- [ ] Download and cache required resources (dictionaries, pre-trained models, etc)

- [X] Use TextChunk instead of plain text

- [X] Extract examples from offline dictionaries

- [ ] Add subtitle (.srt) corpus reader and examples

- [ ] Do try fuzzy matching if no translation found

- [X] Text: write approximate audio timestamp

- [ ] Arbitrary Text Source (book, subtitles, news)

- [X] Generate text output too

- [ ] Make a sequence configurable from a config

- [ ] Fix wordnet for languages differ from English

- [X] Search for collocations

- [ ] Download missing NLTK packages and corpuses automatically if missing

- [X] Fix index before running tasks

- [X] Add synonyms and antonyms

- [X] Use more threads for TTS

- [X] Pickle indices for corpus for quicker start

- [X] Add wordnet: definition (thesaurus, examples, excerpts)

- [X] Update requirements.txt