Is it possible to get localized results with LABEL_DETECTION API?
I want to show the user a result of this API, and some of my users would like to see the results in non-english.
I don't believe that the Vision API can return labels in translated form (though OCR can take in language hints).
That said, you can use the Translate API to come up with a (hopefully) decent localized version of the label name. I know that's far from perfect as translation of single words can be ambiguous, so I'm going to forward this onto the Vision team to see if there's a better answer, maybe using the Knowledge Graph API.
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I am working in an application that gathers a user's voice input for an IVR. The input we're capturing is a limited set of proper nouns but even though we have added hints for all of the possible options, we very frequently get back unintelligible results, possibly as a result of our users having various accents from all parts of the world. I'm looking for a way to further improve the speech recognition results beyond just using hints. The available Google adaptive classes will not be useful, as there are none that match the type of input that we're gathering. I see that Twilio recently added something called experimental_utterances that may help but I'm finding little technical documentation on what it does or how to implement.
Any guidance on how to improve our speech recognition results?
Google does a decent job doing recognition of proper names, but not in real time just asynchronously. I've not seen a PaaS tool that can do this in real time. I recommend you change your approach and maybe identify callers based on ANI or account number or have them record their name for manual transcription.
david
I am now doing an NLP project which needs some resources from twitter.
I want to get those tweets posted by "real people" instead of any kind of "official accounts", including celebrities, ads, institutions, media, etc. such as #CNN #TodayWeather #obama #DailySale #BestPrice #FashionTrend.
Hence, is there a better way to do so?
I have considered about it for a long time. By using twitter's API, the returned JSON includes a key called "verified". This can be used to detect weather an account is that kind of "official account". However, today, this blue "V" tick is not only for those shining celebrities. Anyone can apply for it as long as they are a real person. So, I think using this solution will rule out a lot of precious resources.
Moreover, I also considered using textual spam filter. yeah, of course, they are quite good in most cases. However, some accounts, such as #FT, their posts never sound like a spammy ad. But it is not what I want.
I want to ask for a better solution. It can be a long term solution, such as using NLP and NeuroNets to learn from labels. But, well, a prompt solution will be very welcomed.
THX
I downloaded the EverNote API Xcode Project but I have a question regarding the OCR feature. With their OCR service, can I take a picture and show the extracted text in a UILabel or does it not work like that?
Or is the text that is extracted not shown to me but only is for the search function of photos?
Has anyone ever had any experience with this or any ideas?
Thanks!
Yes, but it looks like it's going to be a bit of work.
When you get an EDAMResource that corresponds to an image, it has a property called recognition that returns an EDAMData object that contains the XML that defines the recognition info. For example, I attached this image to a note:
I inspected the recognition info that was attached to the corresponding EDAMResource object, and found this:
the xml i found on pastie.org, because it's too big to fit in an answer
As you can see, there's a LOT of information here. The XML is defined in the API documentation, so this would be where you parse the XML and extract the relevant information yourself. Fortunately, the structure of the XML is quite simple (you could write a parser in a few minutes). The hard part will be to figure out what parts you want to use.
It doesn't really work like that. Evernote doesn't really do "OCR" in the pure sense of turning document images into coherent paragraphs of text.
Evernote's recognition XML (which you can retrieve after via the technique that #DaveDeLong shows above) is most useful as an index to search against; the service will provide you sets of rectangles and sets of possible words/text fragments with probability scores attached. This makes a great basis for matching search terms, but a terrible one for constructing a single string that represents the document.
(I know this answer is like 4 years late, but Dave's excellent description doesn't really address this philosophical distinction that you'll run up against if you try to actually do what you were suggesting in the question.)
Let's say I'm just wondering around with my cellphone and I want to know exactly which place of business I'm in. This would seem to be easy, but I don't see away to do it. It's possible to reverse geocode but this gives an address range. Google doesn't seem to have http base local search using local information, because you could kind of guess from the local search or points of interest. It needs to be through an http API, not an ajax driven map. Is there a way to do this?
You might look at GeoAPI, which lets you search for businesses near a particular lat/lon coordinate and returns detailed information about the business (name, type, hours, etc.). It's a simple JSON API with good documentation and examples.
There's likely more APIs out there for local business data -- which I personally would love to hear about if people want to add them as answers to this question or comments on my answer. What's your favorite? What are the advantages and disadvantages?
I am trying to develop an online translation service (sort of a personal challenge) but I have been looking for any guidelines or any way to see how it should be done and so far I have come up with nothing so. In a nutshell, does anybody knows where to find a service, code or explanation of how online translation works and/or guidelines for making one?
You could take a look at a similar project: Machine Translation
For a "personal challenge" this project seems way too big. You would need a huge dictionnary and very sophisticated translation algorithms.
Or are you asking if there are APIs to existing translation services?
Decent online translation services work as follows:
Email company with text to translate
They get humans to translate it.
Company sends translated text back in another email
At some point in the above, money exchanges hands.
Automated translation services tend to not work well, due to the huge amount of information required to translate text other than just the text itself, and issues that arise when there isn't an accurate translation for something between 2 languages.
This is a big undertaking. For personal use I use google translate. It does not do a great job, but enough I can get a decent understanding. At work we use COMIDOC, a fairly expensive commercial service. Its not perfect and we have to do a lot of work setting up specialized translations of technical sentences.
You can have a look at the codes of Spanish English, which is an online translation site.