In the comment you say that you want to know "how many homophones there are in the top 2k daily words among at least the top 20 languages" and mention the example of avogado.
It is not clear what exactly how strict you want the match to be, but in any case you are not seeking exact matches per IPA, rather, your question is: how to find exact translations that are cognates or borrowings but not due to the languages being closely related?
(I assume also that you do not care that "no" or "Australia" is the same in Spanish and Italian. I assume also you do not care about words that have been borrowed but taken on a very different meaning.)
If you only care about very common words, then Wiktionary should be a good dataset. It is structured, tends to contain the most common words, and includes translations, cognates and IPA, and has well-known APIs and open source tools like those for Wikipedia. In any case you need to start with a list of most common words in the languages that matter to you, or, at least in one language.
Then (say for a Latin language to Japanese) you can
0. do some pre-processing on the original to make it a bit more phonetic
1. get the translation (hit a translation API like the Google Translate API, or get it from Wiktionary)
2. get Romanisation of (use some lib or get it from Wiktionary) and/or otherwise normalise both original and response (rm accent marks etc)
3. check if they are roughly a match
4. eliminate those that are not interesting to you
5. eliminate those that are just false positives
How check for a rough match? Levenshtein distance above some threshold is a good metric. I might truncate the endings a bit, and normalise for length in some way.
Before we propose how to eliminate those that are not interesting to you, you should clarify what exactly is interesting to you. In general this approach will yield thousands upon thousands of pairs of words that are very boring. (If you visit a longish article on Polish Wikipedia and Ctrl+F for the letter 'f' (which really only occurs in borrowed words), you will find mostly boring words like definicja, flora, fauna... It is a telling sample.)
That said, it is far easier to simply go find good lists like https://en.wikipedia.org/wiki/List_of_Japanese_words_of_Portuguese_origin
But they are not complete, include words where the meaning has shifted, and there are many grey areas for related languages. (Should 99% of Italian be considered as "borrowed from Latin"?)
There are also good heuristics, for example I believe there is really no native Slavic word that contains the letter 'ф', they are all borrowings. In Japanese foreign words are written in a separate alphabet. You can certainly develop a system to detect such words for most languages, it will work the same as language detection (character n-gram frequency).
In any case, this is a massive task, as stealing and borrowing is the way of man.