25 Years In Speech Technology and I still don’t talk to my computer

Re:25 Years In Speech Technology and I still don’t talk to m... by jldugger on Monday October 26, 2020 @02:57PM (#24899779)

The problem, as you note, is that you are actually doing more parsing of the input than virtual assistants do. Tom Scott has some good videos on the subject (https://www.youtube.com/watch?v=m3vIEKWrP9Q&list=PL96C35uN7x...)

To give a more concrete example, here's a UPenn demo (https://cogcomp.seas.upenn.edu/page/demo_view/ShallowParse) for your instagram query:

> NP What percentage PP of NP people can NP you VP detect to be wearing NP masks PP on NP recent Instagram photos VP tagged PP at NP a location PP within NP a 10 mile radius PP of NP Mt. Shasta ?

Part of the reason we don't progress beyond that is that speech recognition like in the OP article is quite bad: 95 percent accuracy is considered "good." But it means we expect 1-2 words of your query to be misrecognized, so even if it did parse the query as you proposed, it would probably be answering the wrong question!

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Re:25 Years In Speech Technology and I still don’t talk to m... by _o-o_ on Monday October 26, 2020 @04:00PM (#24900648)

This reminds me of the issue in machine translation where even sophisticated systems cannot understand the importance of a word like "no". So, for example, a phrase like "please press this button" could be translated as "please do not press this button" and it could be automatically rated as a good translation because most of the words are there.

But, on the other hand, I have dictated these paragraphs, (pretty much just adding punctuation and minor edits at the end). I think the most useful feature I've found related to voice is dictation (speech to text). It is almost perfect, at least in English (and I am not a native speaker).

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