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Good evening,
I'm working on a project with Kinect and I need to perform a gender-recognition using the voice information caught by the microphone of the sensor.
The recognition could also be text-based, i.e. the sentence said by the user could always be the same. I "just" need the binary answer male/female.
I've checked the quite popular open-source Sphinx but I can't understand if it could be used for my needs.
Any idea of what I could use?
Thanks in advance.
For sake of completeness, finally I solved the recognition task without analyzing the voice input.
Gender can be detected with an acceptable precision also by learning and then classifying visual biometric traits. I used speech recognition only as "interface" to activate the demo.
There are several ways to achieve this. You can track pitch (lower pitch values will be male, otherwise female). Or try to build a GMM (Sphinx cannot do this, but HTK can), with one model for male, other for female and another to children.
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I'm working on Sbire which use google speech-api. There is a some things which I don't like with this api.
First, this is not in streaming mode. It receive small audio files but there is no real pipes.
Secondly, it's not precise. Google does not record our voice to learn our accent. I think it's very important to have a good quality of recognition.
I'm looking for a free api or an open-source tool.
Actually there is a streaming mode, but it requires an API key. Here is an example of how to use it: http://mikepultz.com/2013/07/google-speech-api-full-duplex-php-version/
If you want something that learns, you'll need to create a neural network to handle the data. The best open source tool, however, is CMUSphinx or pocketSphinx(a mini version of CMUSphinx). Here is a link to that tool: http://sourceforge.net/p/cmusphinx/code/HEAD/tree/trunk/
The best part of CMU-Sphinx, however, is that you can set a dictionary of keywords. Instead of outputting gibberish, you can have it ONLY output those commands and finds the command closest to what it thinks you are saying. This make speech recognition incredibly accurate, but only work for a small set of words.
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i have open source project done in c++ , it is big and has no documentation
now to "only" to debug it and understand its flow it is possible but very hard.
im looking for well define methods and ways of work , to make this process easier.
like some kind of tools that can help me to draw the objects and class's relationship.
UPDATE
well after digging some more , i know the proper name for this is :
Sequence Diagrams , so i looking how to get Sequence Diagrams out of c++ code
it have to be free tools
here you can find your answer, System Sequence Diagram maybe helps you. if answer not enough tell me to say more details :)
http://www.devcurry.com/2010/03/generate-sequence-diagrams-in-visual.html
and also this link is useful too:
http://weblogs.asp.net/gunnarpeipman/archive/2009/11/20/visual-studio-2010-generating-sequence-diagrams-on-the-fly.aspx
Understand for C++ from Scientific Toolworks has a good reputation. I have no specific experience with it.
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Has anybody seen a resource covering specifically the use of machine vision for locating a human in a room, including cases where they may be partially obscured? I know about OpenCV and other machine vision packages, but I'm looking for a paper/library/code example that focuses solidly on identifying a human in a room; something that is readily integrated into code rather than being a rough idea that would require weeks or months of tweaking or enhancing to do a reasonable job of succeeding at the task. I'd prefer something that does not require binocular vision and can work with a single camera.
First: you should read this about human detection. Then you can find/use opencv code implementing the training step of this kind of detector. You will need to access to a database for training like INRIA Person dataset.
Second: if you need to handle partial obstruction, you may need to implement a human body tracker that can handle this problem. Particle filter could do the work.
If you have problems with implementation feel free to ask more specific questions.
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I am working on a Graduation Project and wondering if anyone can help me with: Benchmark data to load and test on my application.
We are willing to compare between different designs and implementations of different database management systems, and I thought we shall use a standard data set for this task.
Is there any? and if yes, would you kindly show me where to find some, and if there are measures to consider, that would be really helpful.
Thanks in advance.
There are many standard benchmarks. The most famous are the TPC Benchmarks:
http://www.tpc.org/information/benchmarks.asp
Moreover, some researchers publish specific benchmarks. For example, O'Neil et al. avec proposed the Star Schema Benchmark. You need a small and free program to generate the data.
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I'm looking for a Common Lisp implementation I ran across once, sometime in the past year or two. I only remember a few things, and I don't know how to search for it based on these facts, so maybe somebody here can help.
it was open-source, but wasn't one of the big ones (SBCL, CMUCL, MCL, etc.)
it was likely incomplete; it looked almost more like an exercise in writing the simplest possible self-hosted Common Lisp
the main webpage was plain black-on-white, and had 2 columns, where the left column was a link to the source file for a particular area of functionality (loop, format, clos, etc.), and the right column was a link to the tests for that functionality
the source files themselves were pretty-printed for the web, with syntax highlighting that looked kind of like an old Redhat Emacs default config: slate-gray background, etc.
Where can I find this Lisp implementation?
Thanks!
I don't know which one you are referring too, but you can find a list of Common Lisp Implementations here.
Is there any particular reason why this Lisp is grabbing your attention now?
Its hard to pin down, but open-source + minimalistic + incomplete sounds vaugely similar to Paul Graham's Arc programming language.