Is/are there existing C++ NLP API(s) out there? The closest thing I have found is CLucene, a port of Lucene. However, it seems a bit obsolete and the documentation is far from complete.
Ideally, this/these API(s) would permit tokenization, stemming and PoS tagging.
Freeling is written in C++ too, although most people just use their binaries to run the tools: http://devel.cpl.upc.edu/freeling/downloads?order=time&desc=1
Try something like DyNet, it's a generic neural net framework but most of its processes are focusing on NLP because the maintainers are creators of the NLP community.
Or perhaps Marian-NMT, it was designed for sequence-to-sequence model machine translation but potentially many NLP tasks can be structured as a sequence-to-sequence task.
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Maybe you can try Ellogon http://www.ellogon.org/ , they have GUI support and also C/C++ API for NLP too.
if you remove the restriction on c++ , you get the perfect NLTK (python)
the remaining effort is then interfacing between python and c++.
Apache Lucy would get you part of the way there. It is under active development.
Maybe you can use Weka-C++. It's the very popular Weka library for machine learning and data mining (including NLP) ported from Java to C++.
Weka supports tokenization and stemming, you'll probably need to train a classifier for PoS tagging.
I only used Weka with Java though, so I'm afraid can't give you more details on this version.
There is TurboParser by André Martins at CMU, also has a Python wrapper. There is is an online demo for it.
This project provides free (even for commercial use) state-of-the-art information extraction tools. The current release includes tools for performing named entity extraction and binary relation detection as well as tools for training custom extractors and relation detectors.
MITIE is built on top of dlib, a high-performance machine-learning library, MITIE makes use of several state-of-the-art techniques including the use of distributional word embeddings and Structural Support Vector Machines[3]. MITIE offers several pre-trained models providing varying levels of support for both English and Spanish, trained using a variety of linguistic resources (e.g., CoNLL 2003, ACE, Wikipedia, Freebase, and Gigaword). The core MITIE software is written in C++, but bindings for several other software languages including Python, R, Java, C, and MATLAB allow a user to quickly integrate MITIE into his/her own applications.
https://github.com/mit-nlp/MITIE
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Are there to day any concept mining open source tools available? I have only be coming across like Leximancer, which although seem to fit the role is not open source and quite expensive for a undergraduate student. I have been unsuccessful so far since the word 'concept' on both google and google scholar seems to be un-matching what I want.
It seems to me you need a text mining tool for clustering. RapidMiner has an open-source, Java based Community Edition which has several extensions (Text Mining, R, etc.). In addition you can develop and integrate your own algorithms too.
Moreover Rexer Analytics offers a comprehensive data mining survey annually, you can call for reports for free.
I am working on a very basic robotics project, and wish to implement voice recognition in it.
i know its a complex thing but i wish to do it for only 3 or 4 commands(or words).
i know that using wavin i can record audio. but i wish to do real-time amplitude analysis on the audio signal, how can that be done, the wave will be inputed as 8-bit, mono.
i have thought of divinding the signal into a set of some specific time, further diving it into smaller subsets, getting the average rms value over the subset and then summing them up and then see how much different they are from the actual stored signal.If the error is below accepted value for all(or most) of the sets, then print the word.
How can this be implemented?
if you can provide me any other suggestion also, it would be great.
Thanks, in advance.
There is no simple way to recognize words, because they are basically a sequence of phonemes which can vary in time and frequency.
Classical isolated word recognition systems use signal MFCC (cepstral coefficients) as input data, and try to recognize patterns using HMM (hidden markov models) or DTW (dynamic time warping) algorithms.
You will also need a silence detection module if you don't want a record button.
For instance Edimburgh University toolkit provides some of these tools (with good documentation).
If you don't want to build it "from scratch" or have a source of inspiration, here is an (old but free) implementation of such a system (which uses its own toolkit) with a full explanation and practical examples on how it works.
This system is a LVCSR (Large-Vocabulary Continuous Speech Recognition) and you only need a subset of it. If someone know an open source reduced vocabulary system (like a simple IVR) it would be welcome.
If you want to make a basic system from your own, I recommend you to use MFCC and DTW:
For each target word to modelize:
record some instances of the word
compute some (eg each 10ms) delta-MFCC through the word to have a model
When you want to recognize a signal:
compute some delta-MFCC of this signal
use DTW to compare these delta-MFCC to each modelized word's delta-MFCC
output the word that fits the best (use a threshold to drop garbage)
If you just want to recognize a few commands, there are many commercial and free products you can use. See Need text to speech and speech recognition tools for Linux or What is the difference between System.Speech.Recognition and Microsoft.Speech.Recognition? or Speech Recognition on iPhone. The answers to these questions link to many available products and tools. Speech recognition and understanding of a list of commands is a very common problem solved commercially. Many of the voice automated phone systems you call uses this type of technology. The same technology is available for developers.
From watching these questions for few months, I've seen most developer choices break down like this:
Windows folks - use the System.Speech features of .Net or Microsoft.Speech and install the free recognizers Microsoft provides. Windows 7 includes a full speech engine. Others are downloadable for free. There is a C++ API to the same engines known as SAPI. See at http://msdn.microsoft.com/en-us/magazine/cc163663.aspx. or http://msdn.microsoft.com/en-us/library/ms723627(v=vs.85).aspx
Linux folks - Sphinx seems to have a good following. See http://cmusphinx.sourceforge.net/ and http://cmusphinx.sourceforge.net/wiki/
Commercial products - Nuance, Loquendo, AT&T, others
Online service - Nuance, Yapme, others
Of course this may also be helpful - http://en.wikipedia.org/wiki/List_of_speech_recognition_software
I want to know about various techniques to do speech recognition and text to speech conversion.
Also please let me know about any resources like links, tutorials ,ebooks etc. on it.
Which is the most efficient technique to achieve it ?
I'm going to answer the part about speech recognition (since I don't know much about text-to-speech):
http://ecx.images-amazon.com/images/I/4190SZC61CL._BO2,204,203,200_PIsitb-sticker-arrow-click,TopRight,35,-76_AA240_SH20_OU01_.jpg
This book, "Statistical Methods for Speech Recognition" is a classic that explains the mathematical foundations of statistical speech recognition, written by the founder of that area, Frederick Jelinek.
The most important concept you have to know is Hidden Markov Models. People have been using them in speech recognition for decades. A recent approach uses Conditional Random Fields, see the paper (PDF) and the associated software toolkit SCARF.
It is fairly hard to write your own speech recognizer. It's an active research area with several scientific conferences, e.g. ASRU, Interspeech, ICASSP.
Both are very wide areas.
About recognition: In this this schema you will find how to build a basic automatic speech recognition system. It isn't by any means close to the start of the art, but it is something achievable and it works. If you want to do something more advanced, read about cepstral coefficients and Hidden Markov Models. Have a look into HTK, it is a widely used toolkit for Hidden Markov Models.
About text to speech: I'd have a look at Festival.
There are multiple sphinx's. The main active ones are pocketsphinx and sphinx4.
Sphinx4 is written in Java. It is better for desktop and web applications.
Pocketsphinx is written in C. It is better for embedded devices. There are iphone/android apps that use it.
Sounds like you want pocketsphinx. Try out this tutorial:
http://www.speech.cs.cmu.edu/sphinx/tutorial.html
A better place to ask pocketsphinx/sphinx4 questions is on CMU's sourceforge forum.
Also you should provide more info like what you intend to make.
As for books, the bible of speech recognition is "Spoken Language Processing"
Since you mentioned MS -
You should just look at the Microsoft Speech site. It contains many resources for dealing with speech, including TTS and speech recognition.
If you're looking for some actual code, check out Sphinx, an open source speech recognition project from CMU. It's not written in C++, but if you're interested in algorithms, it's implemented a bunch of stuff you can learn from. (I'd like to echo #dehmann's point, too: read up on hidden markov models.)
If you are curious about what to do with your fancy speech recognition you should read:
Voice Interaction Design by Randy Allen Harris
It provides some great advice about when to use Voice and how to use it in an application.
I'd like to try out OpenGL programming in Scheme.
Can anyone give a recommendation for a decent Scheme compiler / OpenGL library combination?
I have no reservations, though it would be nice (but not a requirement) to be able to produce native, executable binaries — primarily on Windows, but also on UNIX and/or Mac OS X.
EDIT: Changed to community wiki, since the question does not have a definite answer I can accept. Thanks for the replies!
PLT Scheme includes OpenGL bindings in 2 forms, one that matches the C API, and one that's more "scheme" like in usage.
Update: PLT Scheme is now known as Racket, which also has OpenGL bindings.
Chicken Scheme has an egg that provides OpenGL bindings. IMHO, it's not well documented; if you are not familiar with OpenGL already, then this library isn't the right place to start learning.
Spark Scheme:
Spark-Scheme is a dialect of Lisp, which gives you...
Interactive, modular software development
Meta-programming facilities
Advanced control flow
Distributed computing
A comprehensive networking API
A modern GUI framework
2D/3D graphics
An SQL database engine and connectivity to third-party databases
A web server and a couple of web application frameworks
Gambit-C Has some "3rd party" Open GL bindings, available in the dumping grounds.
I have a large MFC C++ application that I would be very keen to port into AutoCAD and IntelliCAD. AutoDesk offer Object ARX for this purpose, which replaces the older and slower ADS technology. IntelliCAD, afaik only supports ADS. Has anyone out there done this, and if so which tools did you use and what pitfalls did you encounter?
I'm specifically interested in resources that will simplify the transition, and allow me to maintain seperate CAD based and standalone versions going forward.
Have a look at my answers to a couple of previous AutoCAD questions
Open source cad drawing (dwg) library in C#
.Net CAD component that can read/write dxf/ dwg files
If you were looking for the same code base to work both inside and outside of AutoCAD then the RealDWG approach may work for you since the code is the same - RealDWG doesn't need AutoCAD as a host application. The open Design Alliance libraries are for making stand-alone applications. Both have supported C++ for years & can be considered stable - well, as stable as CAD gets.
This blog (http://through-the-interface.typepad.com/) is a good one for RealDWG
One option to consider is to target AutoCAD and Bricscad. Supporting AutoCAD and IntelliCAD requires essentially two versions of code. Bricscad's goal is to be completely compatible with ObjectARX, and in my experience they are pretty close.
This at least simplifies the problem from supporting three instances (your standalone version, AutoCAD, and IntelliCAD) to supporting two instances (your standalone version and AutoCAD/Bricscad).
"DWGdirect is not just a SDK to read and write DWG files. It actually offers a full blown framework that can be used to develop a professional CAD application, complete with plug-in architecture and all." quote source