World's most boring audiobook: German-English text-to-speech

A lot of my projects involve a great deal of I wonder what the result might look like. This one was not unexpected

A few days ago I quickly hacked a pocket translator using a M5Cardputer and the WikDict SQLite dictionaries.

Thinking about what else I could do with these databases, I had a stupid thought:

Let’s make an audiobook of German to English words.

I hadn’t done any TTS in… ages, luckily with the help of Gemini I could find a decent modern library I could run locally… After failing with espeak-ng, which does not work well on Mac and Mozilla TTS, which has few models and is unmaintained. I ended up using Coqui TTS, and two TTS models (one for English and one for German) that work reasonably well.

Input data preparation

The first thing was preparing a list of the most important German words, out of the wikdict databases.

sqlite3 de-en.sqlite3

Supposedly the column importance in the de-en.sqlite3 database measures some sort of proxy of it.

CREATE TABLE translation(
  lexentry TEXT,
  sense_num TEXT,
  sense,
  written_rep TEXT,
  trans_list,
  score,
  is_good,
  importance
);

I wanted the German nouns to come together with their adjective… and otherwise get the part of speech. It is good to know if something is a verb or an adjective. This information is in the de.sqlite3 database

ATTACH DATABASE 'de.sqlite3' AS de;

SELECT DISTINCT 
  t.lexentry,
  t.written_rep,
  t.trans_list,
  e.vocable,
  e.part_of_speech,
  e.gender,
  t.importance FROM translation AS t
  JOIN de.entry AS e
  ON t.lexentry = e.lexentry
  ORDER BY importance DESC
  LIMIT 10;

This looked reasonably good, so I created a separate sqlite3 file with this:

ATTACH DATABASE 'top_de.sqlite3' AS top;

CREATE TABLE top.top AS 
SELECT DISTINCT 
  t.lexentry,
  t.written_rep,
  t.trans_list,
  e.vocable,
  e.part_of_speech,
  e.gender,
  t.importance FROM translation AS t
  JOIN de.entry AS e
  ON t.lexentry = e.lexentry
  ORDER BY importance DESC
  LIMIT 10000;

Top 10000 words looks reasonably large but not overwhelming. But, if you think about it, at 5 seconds per word this is going to be around 15 hours. Not the most exciting “audiobook”.

Audio file generation

I got Gemini to write most of this. Although I set it up as a poetry project, I’m posting it as a script here. You will need to install TTS (capitalised) and pydub:

If you happen to run this, it might take a while: took my Mac M1 around 5 hours to generate the 4GB of wav files.

Final cleanup

To wrap up (I could have done this in Python, but did not bother), I grouped the resulting wav files in folders with 1000 files and converted them to concatenated mp3:

for f in *.wav; do echo "file '$f'" >> input.txt; done # Avoid issues with spaces and long commands
ffmpeg -f concat -safe 0 -i input.txt -c:a libmp3lame -q:a 4 file.mp3

If you do this, you will end up with around 14 hours of todlangweilig audio.

• Python
• German