But: fundamentally, why did all of this happen, and why haven't prices normalised (i.e. dropped) since?
Does anyone have a hypothesis, beyond 'corporate gouging', which I can accept, but seems too simplistic to explain what seems to be an enduring global phenomenon?
Many things were technically feasible pre-pandemic but not done habitually: remote work, streaming movies instead of going to the theater, ordering delivery instead of dining out, and so on. The pandemic forced many people to change their habits and get over any initial inertia (e.g. investing in a WFH setup or home theater). The result is that when the world returned to normal, the markets didn't: consumer habits had already moved on.
This is not very close to true. English (even a given accent) has a rather high number of phonemes, and they don’t overlap very closely with Hindi. What is probably more relevant here is that Devanagari is relatively phonetic so writing in it is useful to describe English pronunciations, more so than the English script is for Hindi (or English, for most unfamiliar words).
A very incomplete list of languages by approximate number of phonemes: https://en.wikipedia.org/wiki/List_of_languages_by_number_of...
It's true that the English language has a very large number of phonemes... but accents tend to regularize/restrict these phonemes. For example, a typical bilingual speaker of Indian English and Hindi will replace instances of the /æ/ phoneme (as in "blast" or "fast") with another phoneme like /a:/ (as in "father"). Which isn't that unusual since /æ/ is pretty uncommon among languages.
Other rare English phonemes include the dental fricatives, i.e. the "th" sounds in "ether" (voiceless) and "either" (voiced). Speakers of Indian English often replace this with a dental stop, a "t" sound (voiceless) or "d" sound (voiced). (Note that Devanagari has a _lot_ of stops, so this is one place where it cannot be cleanly encoded into the Latin alphabet without diacritics.)
So overall: while I think Devanagari can't encode e.g. American English, it can actually do a pretty solid job of encoding Indian English, but not the other way around.