I wanted to try the currency converter feature of bixby where i ask it to convert the value from lets say USD to INR. This feature was in earlier updates of bixby. But when i tried it now, it wont work. If anyone could help me that would be great.
Thanks
Depending on how your questions is phrased, you should be presented a list of capsules that can address your use case.
For example, asking, "What is 50 Dollars in Indian Rupees" provides me with a list of two capsules that can serve this request. When I select one (I arbitrarily chose CNBC), I get the answer I requested, "50 U.S. dollars are equal to 3751.5 Indian rupees".
Related
I'm new to NLP.
I want to extract music artist's name from plain text like that is posted on social media.
The text looks like this. (this is just sample, not real)
Today bandcamp is waiving fees again! CHANGE, TAYLOR SWIFT and POP
SMOKE will be using all funds collected through bandcamp to donate to
Anti Repression Committee. No Justice No Peace.
This time,I want to extract string "CHANGE","TAYLOR SWIFT","POP SMOKE".
I already tried NLTK and spaCy but it didn't work as desired.
Is there any other idea how I can achieve this?
Thanks in advance.
If you have a lot of upper case data like in your example, you might want to pass the data through a truecaser first. There’s one available in the Stanford NLP package. After that, spacy might have a better shot at picking the names out. On this text:
Today bandcamp is waiving fees again! Change, Taylor Swift, and Pop Smoke will be using all funds collected through bandcamp to donate to Anti Repression Committee. No Justice No Peace.
en_core_web_sm will pick out Taylor Swift and Pop Smoke as entities. Change / CHANGE is going to be tough for any model to pick out.
I'm trying to allow users to say a dollar amount as input to a Bixby capsule.
So I made a concept of type money.Currency:
structure (Amt) {
role-of (money.Currency)
description (Amount to spend)
}
And then I gave some training examples using it:
[g:SomeGoal] I want to pay {[g:Amt] ($)[v:viv.money.PrefixSymbol:$](25.32)[v:viv.money.CurrencyValue]}
This works fine when the user enters their dollar amount in text, but it frequently fails if the user tries to speak the amount aloud to Bixby.
Example 1 (fails): The user says "I want to pay twenty-five dollars thirty-two cents." Bixby parses this as "I want to pay $25 32 cents" and populates the Amt field with just $25, leaving out the cents.
Example 2 (fails): The user says "I want to pay twenty-five thirty two." Bixby parses this as "I want to pay 2532" and populates the Amt field with $2532, again failing to fill in a value for the cents.
Example 3 (succeeds): The user says "I want to pay twenty-five point three two dollars." Bixby correctly parses this as "I want to pay $25.32" and fills in the Amt field with $25.32. This sounds very unnatural for English speakers though, and I do not think it will be easy to train users to speak this way.
Example 4 (sometimes succeeds): The user says "I want to pay twenty-five dollars and thirty-two cents." Bixby sometimes parses this correctly, other times as "I want to pay $25 in 32 cents" or other similar corruptions.
Anybody have suggestions for getting Bixby to consistently understand dollar amounts in natural language? I am okay with example 2 failing since it is ambiguous, but mainly I would like examples 1 and 4 to succeed consistently. I do have one idea for a workaround (a separate cents field that's manually added to the dollars field by an action), but I'd prefer to avoid that if possible since this seems like a common case that Bixby should be able to handle on its own.
Thank you for bringing this to our attention. I tried the following sentence "Pay one hundred dollars and 25 cents" multiple times and Bixby was able to transcribe it accurately every time.
But your use case (especially #1) is valid as some users tend to not use "and" to tie dollars and cents together. We will raise this internally with our team but I would suggest that you open a ticket with Bixby Developer Support so we can tie your ticket with the issue and keep you posted when its fixed.
Also, your workaround of using a second property to capture cents should work fine too. Let us know if you run into any issues.
Im tring to create a booking system for a restaurant so the assistant go to ask to user number of guest, time and day to reserve, and finally the name and the phone number of guest! But many time the phonenumber is confused by the guest number.
I set in parameters for #guest the value of #sys.number and for $telephone the entity of #sys.phone-number, but sometimes get wrong recognize. I could make it work?
The Dialogflow team has a really full-featured example on Github here (it's a bike shop, rather than a restaurant, but most of the functionality is the same). Give it a look for some inspiration.
Regarding the specifics of recognizing phone numbers: I'd recommend adding a bunch (like more than 10) of example training phrases to the appropriate Intent that include phone numbers. Often the problem with matching these things is just a matter of the number of examples the system gets to learn from.
Good luck!
Is there an effective Natural Language Processor that can fetch the phone number and date of birth from human speech. Each user has a different way of specifying the phone number and date of birth. Hence, converting speech to text and then parsing the text for phone number is not helpful.
You can use Google speech to text api. I had used same for entering account number for blind people. I was working for bank so I there were lots of numbers involved as input eg account number, card number etc.
With Google STT engine you can define custom voice inputs.
Also I had created feedback mechanism using Text to Speech Api so that app can tell if users feedback is invalid and request him to speak again.
You can see code snippet at github.
https://github.com/hiteshsahu/Android-TTS-STT
Easiest way is to extract text from speech, there is plenty of tools, proprietary (nuance), and tinker friendly open source like sphinx, and plenty of tools to extract dates and phones expressed differently. IBM Watson offers one, Smart Formatting beta, to uniform dates and phones in own transcripts. To guess which dates are birthdays you try detect related keywords (birth, born so on) nearby.
For few free alternatives, check
For phone #
https://www.npmjs.com/package/phone-number-extractor
https://github.com/googlei18n/libphonenumber
For date extractions check prev questions
Extracting dates from text in Java
Best way to identify and extract dates from text Python?
There is a patent for the process your are asking, but you might have to pay royalties or smth.
http://www.freepatentsonline.com/8416928.html
If you want to fetch the phone number and date of birth from human speech.
So, you can use another option and implement it.
https://cloud.google.com/speech/
This API is really useful for converting your speech to text. I also have this problem at one moment so you can try it too.
The another API which is really good for authentication.
https://api.ai/
I hope it helps you.
I am designing an autosuggest feature on a quick-search box. Suggestions will include small icons, multiline text, etc. The application is handling orders. The search field will recognize a variety of different meaningful terms - e.g. customer surname, order id, etc. But when an order ID is input, I want users to get an opportunity to view either the order, or the person. I was thinking that I would like a hierarchy within the list - so if i type 1234, and it matches 5 orders for 3 different people, the 3 people are returned at the top level, and their 5 orders underneath the respective customer.
Quick mockup:
Has anyone seen something like this implemented elsewhere? Don't want to re-invent the wheel. Also interested in any other feedback.
Answer to your question: No, haven't seen this elsewhere.
Feedback on your mockup:
I would say that it is a pretty creative autosuggest solution.
However, I think it is overkill though. If I just want to quickly navigate to the Order page by searching a specific Order ID (and expecting only one result in the autosuggest), but the autosuggest shows up five order items under three people (as shown in your mockup), I think that is way too much, put aside performance.
My idea:
Each autosuggest item contains one Primary Line that can clearly identify the item and additional Details Line(s) that provide more description about the item, similar to Google's search result page and Facebook search autosuggest.
For example, the autosuggest shows up each item like this when users search for an order:
(Order Icon) 23-34534
Loaf of Bread, Soda and more.
By Bob Jones, Paul Smith and others.
You can make each order item (Loaf of Bread, Soda, more) link to the respective order item line in the Order page, and each person name to the respective person page. This method is more concise and takes less space than your mockup while still providing the functionality that you want.
Sometimes, simple is better, less is more. Remember the KISS principle. Think of Apple iPod and iPhone as examples.