I am studying about artificial intelligence
How did the virtual assistants analyze questions?
Example: when I said "Way from New York City to Washington DC" , va opened google map?
If I would develop that stuff myself I'd probably would use pattern like
If ({a} {linker} {b}) where a and b are in list of cities on map or something related to that and linker is word like "from" or "to" i would run google maps with, also if any of remaining words would signal that it is map related stuff, like "location", "map", "route" and so on...
Just a guess but I think this should work like that
I don't have any idea that which programming language will you prefer to develop this project but I highly recommend Python. It is object-oriented, high level and extensive support libraries. Moreover, I don't know what is your targeted OS for this project, you unfortunately have not specified it and maybe you will choose Android OS(for mobile application you may use Python) so Python may not be a good option for you. But I supposed that you will develop a desktop application so I will propose my opinions under the motivation that you will choose Python to develop this project.
First of all, you can use speech recogition library for speech to text. After getting text from speech, we can jump to next step which is analyzing the questions.
At the present time, deep learning is the state of the art and Tensorflow is the great technology to take advantage of deep learning.
This is an amazing chatbot framework to build a conversational model for your custom chat bot. You should edit this JSON file to create your conversational intents, after the editing JSON file, you can analyze the questions of user (i.e. your program can understand what user said, the program will parse the question and get the location which is requested by user). When you get the location from question, the program can open browser (for example GoogleMaps) via executing an Ubuntu terminal command in Python.
As a summary, when user says "Way from New York City to Washington DC" the program will run respectively;
Get text from user speech
The program will analyze text via trained system and it can understand that what user said
The program can get the destination and current location which is specified by user (many kind of information can get from user request) by using the structure of this JSON[I recommend this way], or may be NLP or using any kind of string operations
The program will start to load Google maps URL via (for example) Ubuntu terminal command for these location information
Related
I am new in reactjs and I have a task in hand. I need to be build and application which is capable to scan a mykad(Malaysian ID card) through camera. Details like name, address, image can be extracted. I googled a bit about open source tesseract but it is not giving me the right information and also some of the informations are misspelled. If anyone can guide me in the right direction.
Eventually I will develop a PWA and deploy in mobiles as well
If you're looking for a free solution, Tesseract.js is your way to go: https://tesseract.projectnaptha.com
You need to be aware that reading data from MyKads will not only require OCR component, but also specifying semantics for the document. Meaning, you'll need to tell tesseract where the name is, where the address is, etc.
Also, tesseract will not be able to detect the document on the image. For this you'll need to use a different tool.
Disclaimer: I'm working at Microblink where we develop commercial OCR products, including one for reading data from IDs. For PWAs we have an JavaScript / TypeScript component which uses WASM to process the IDs. It supports not only MyKads but more than 500 document types in the world.
Github link: https://github.com/BlinkID/blinkid-in-browser
I want create and train own model. If not possible to create own, any way to train other models? (Yolo, MobileNet, Coco?)
There some requirements:
- I know only JS (tried Python, no, i don't continue, i can't, Python best language, but i can't, sorry)
- Performance, at least 24 FPS, like real-time detection
- Own dataset freedom (like file /dogs/pitbull/01.png)
I tried Python, but i don't/can't work in Python due of 10 years experience with JS doesn't lets me use Python
Thanks for everyone for help
This answer is written by an IBMer.
If you want to build a model like the one described (image classification/object detection) without having to deal with python - and you want to use it with javascript in a browser, you can try the tooling available at https://cloud.annotations.ai/. It works with a IBM Cloud account but you can stay go on with the free tier - so you just need to register, at least to do your first experiments.
You'll find here https://github.com/cloud-annotations code and boilerplate to use your model on different platform.
It is not an advanced tool but it enables you to put your hands on the topic.
Is it possible to restrict and AVS device (a device running Alexa) to a single skill? So if I built an AI skill and have it running on a device, is it possible to keep the experience inside the custom skill so I don't have to keep saying Alexa, open
One trick you can do with AVS is to prepend every single request with a sound clip equivalent to: "ask to ..." It's definitely a hack, but I was able to use it with some success.
See my write-up here: https://www.linkedin.com/pulse/adding-context-alexa-will-blaschko-ma
The relevant parts (in case the link goes away).
Regular voice commands don't carry my extra information about the
user, but I wanted to find a way to tack on metadata to the voice
commands, and so I did just that--glued it right onto the end of the
command and updated my intents to know what the new structure would
be.
...
In addition to facial recognition, voice recognition could help
identify users, but let's not stop there. Any amount of context can be
added to a request based on available local data.
“Find frozen yogurt nearby" could silently become “Alexa open Yelp and
find frozen yogurt near 1st and Pine, Seattle” using some built in
geolocation in the device (phone, in this case).
I also use something similar in my open source Android Alexa library to send prerecorded commands: https://github.com/willblaschko/AlexaAndroid
I think you are looking for AWS Lex which allows you to write Alexa like skills without the rest of Alexa feature set.
http://docs.aws.amazon.com/lex/latest/dg/what-is.html
I've to write a program which is able to recognize patterns, specially characters. I've implemented back-propagation in c# and now I want to use it for the pattern recognition. I've also created a form application and used brush/graphics so that user can write something with the help of mouse (just like 'pencil tool' in MS Paint). So I need some helping material about "How to implement character recognition method in my application?".
Helping stuff over the internet mostly related to back-propagation and software demos.
If your project is something else but you want to have OCR in your project, you should search for third party tools that do this. But if your project is this and you want to do that yourself, read this answer:
There are two ways of recognizing characters. Online and offline.
Online way uses the pen (or mouse) input data. and offline way uses just the pixels.
Your first step will be choose from one of them. offline way hasn't the pen data, this is a useful feature. but in offline, you can recognize characters from image files (created by paint and saved or even scanned)
Second, you should preprocess data (this step is for only offline way). you should remove noises from it, scale it, and do the Thinning to it.
Next, you should extract useful features from the preprocessed data (online or offline). for this, you can read some articles about optical character recognition and feature extractions of it. there is a good powerpoint presentation about preprocessing and feature extraction here. Also pdf keyword and filetype:pdf at the end of your search term in google would help you!
Then you should use neural networks or something like that to recognize the character. inputs should be extracted features.
But remember, this project is not easy and may take some time! (This was my project for Persian language)
Preface: I have a broad, college knowledge, of a handful of languages (C++, VB,C#,Java, many web languages), so go with which ever you like.
I want to make an android app that compares numbers, but in order to do that I need a database. I'm a one man team, and the numbers get updated biweekly so I want to grab those numbers off of a wiki that gets updated as well.
So my question is: how can I access information from a website using one of the languages above?
What I understand the problem to be: Some entity generates a data set (i.e. numbers) every other week and you have a need to download that data set for treatment (e.g. sorting).
Ideally, the web site maintaining the wiki would provide a Service, like a RESTful interface, to easily gather the data. If that were the case, I'd go with any language that provides easy manipulation of HTTP request & response, and makes your data manipulation easy. As a previous poster said, Java would work well.
If you are stuck with the wiki page, you have a couple of options. You can parse the HTML your browser receives (Perl comes to mind as a decent language for that). Or you can use tools built for that purpose such as the aforementioned Jsoup.
Your question also mentions some implementation details such as needing a database. Evidently, there isn't enough contextual information for me to know whether that's optimal, so I won't address this aspect of the problem.
http://jsoup.org/ is a great Java tool for accessing content on html pages
Consider https://scraperwiki.com/ - it's a site where users can contribute scrapers. It's free as long as you let your scraper be public. The results of your scraper are exposed as csv and JSON.
If you don't know what a "scraper" is, google "screen scraping" - it's a long and frustrating tradition for coders, who have dealt with the same problem you have since the beginning of networked computing.
You could check out :http://web-harvest.sourceforge.net/
For Python, BeautifulSoup is one of the most tolerant HTML parsers out there. The documentation also lists similar libraries in Ruby and Java, so you'll probably find something relevant there.