I'm a totally blind individual who would like to learn more of the theory aspect of computer science. I've had an intro data structures class and the general intro programming but would like to learn more on things such as software design, advanced data structures, and compiler design. I want to do this as a self study course not as part of college classes.
Unfortunately there aren’t many text books available on computer science from Recordings for the Blind and Dyslexic where I normally get my textbooks. I would appreciate any electronic resources preferably free that could help me get more of a computer science education rather then the newest language or platform that a lot of programming sites appear to focus on.
You might find the Experiences of a Blind Computer Scientist a good read.
MIT's Open Courseware would be a good resource for you with the amount of videos/audio they have.
Really though, for the core computer-science topics I find it pretty hard to beat some of the better textbooks out there. Some offer digital versions of their book with purchase and some don't. For those that don't, I would just purchase the book and then download via a torrent site a digital e-book equivelant. Since you already own the book I don't think this would be a major problem.
UC Berkley has a couple of computer science courses online for free as mp3 and video files (including RSS feed for each course). And if reading PDF files aren't an issue you could check out O'Reilly's Safari.
The text book for Structure and Interpretation of Computer Programs appears to be accessible. Software engineering radio is a good podcast that I listen to but recently has focused a lot on model driven development and UML which doesn't interest me. The UC Berkley
lectures are of varying quality, it's like all other college classes it depends on the professor. I've found I can follow along with the cs162 lectures fine but not so much with the cs61b. Part of this is because of the professor and part is probably because 61b is more math heavy since it's a data structures class. Unfortunately the RSS feeds are useless since the file names are meaningless. I used my podcatcher to download the entire lecture series, then used the converting capability of foobar 2000 to rename the files with there track number so I could listen to them in order. I've used Safari at work before and it is accessible although to expensive for me to get a yearly subscription. Open Courseware appears to have a lot of good stuff. Unfortunately I don't use itunes so instead of downloading each mp3 file individually I used the firefox extension DownThemAll! with a custom filter to grab all the mp3 files at once from the specific course I wanted. Another series of books that looks useful are the data structures books by Bruno R. Preiss several of which are available online at
http://www.brpreiss.com/books/opus5/
Some of the equations are represented as graphics but I can often tell what the general idea is by context.
I wonder would the Structure and Interpretation of Computer Programs video lectures by Hal Abelson and Gerald Jay Sussman be of any use?
If the audio content is enough on its own without the video, they are an excellent digital resource.
The podcast "software engineering radio" is excellent. Though not CS courseware, it is the most academic and intellectually stimulating podcast I have found about software development and computer science.
http://www.se-radio.net/
personally I am just blown away by the questioner. I mean, the challenge alone of programming is too much for most people but being without the primary sense used in the task is amazing to me. What is ironic though is I bet that given this challenge the questioner is still FAR more adept at most CS tasks than the people I work with day to day. Just saying.
I'm also a totally blind programmer, currently working for Microsoft. The most valuable resource for te technical books is Safari (safari.oreilly.com). You can read thousands of computer science texts there. if you're in the USA, you can also get many of those titles for free from BookShare (www.bookshare.org). In both cases graphical images will be an issue, but there's no easy solution for that. Most good books have enough descriptive text that one can manage without the diagrams.
I to am a new blind programmer! I only lost my vision 5 years ago. Anyway, I have been programming in Visual Basic 2008 throughout the past year. It turned out to be more accessible than I had at first suspected.
I start a Java class next semester and the required text is a free online text! It is posted below.
Introduction to Programming Using Java, Fifth Edition
http://math.hws.edu/javanotes/
Can some of you seasoned blind programmers share with us any blogs or websites where other blind programmers can be found??
Check out this Stack Overflow question about podcasts.
A language called Quorum is a lot like Python but optimized across a few more syntactic details, and the corresponding development environment is designed with the blind in mind. https://quorumlanguage.com/ This might fit especially well with the use case where most students are using Python.
A 2016 blog about CSed (actually a response to a blog post) points to
program-l discussion board for blind programmers at https://www.freelists.org/list/program-l
The EPIQ conference for blind and other programmers interested in Quorum
https://quorumlanguage.com/epiq.html
Also, see other ideas in a similar question on another SO site: https://cseducators.stackexchange.com/questions/3441/teaching-a-blind-high-school-student
Related
I have been programming in a "learn-by-doing" fashion for almost 2 years now and I consider myself fairly good however, I really wish to build a good foundation of Computer Science/Computer Engineering and most people recommend I start off with SICP. (Structure and Interpretation of Computer Programs)
I wished to know
Is this the best way to go about it?
I know how to code a matrix-multiplication in OpenMP and MPI and I know college level math, is this sufficient to read and appreciate SICP?
Instead of this, can I just spend all my time working on Project Euler instead?
A personal experience: Like you I am trying to learn programming by self-study and I started off with SICP. As I am a ancient historian and archaeologist, I have no background in maths, engineering or real computer science (just good knowlegde in stuff like LaTeX, HTML and CSS). My last lessons in math are now 15 years ago. Although I am working through SICP with a math book at my side the explanations given in SICP are really sufficient to understand the stuff. I really appreciate SICP, it is demanding, but great fun. I also would recommend to buy it as a book, I prefer that from reading on screen.
Sometimes you have to cope with some difficulties because language standards have changed (eg. Running SICP Pattern Matching Rule Based Substitution Code) or the authors assume existing functions which are just defined later in the book (eg. How do I get the functions put and get in SICP, Scheme, Exercise 2.78 and on). As a you always will find solutions or hints on the web this is nothing which should bother you.
If you know any amount of programming you'll likely be better off for it, but it's by no means a requirement when going through the SICP. I'm going through it right now (cover to cover style), and I'm up too section 2.3.3. The biggest road block for me has been how maths based some of the problems can be, as it's been a while since I did maths back in high school. For these problems I've resorted to googling an explanation of the problem and solution. Like programming, maths isn't a requirement either, obviously because I'm still making progress through the book, but I feel it could help at times.
The only requirement you'll honestly need, is a computer and a scheme implementation, I'd recommend MIT scheme or DrRacket.
TL;DR
The only requirement you'll need is a computer, and a scheme implementation, everything else can be learned as you go along.
I'm about to start my honours project at uni on OpenCL and how it can be used to improve modern game development. I know there is a couple of books out now/soon about learning opencl but I was wondering if anyone knows any good papers on opencl.
I've been looking but can't seem to find any. Part of my project requires a literary review and contrast so any help on this would be appreciated.
I'll not point you directly to any papers, instead I'll give you a few hints on where to look for them.
Google scholar, One of the best places on the web to search for papers on any subject. Searching for "opencl game development" turned up a few interesting results right on the first page; for sure there are other valuable results in the following pages.
IEEE Explore; IEEE is one of the de facto establishments on all thing computer and electronics; their journals and conferences have many publications on OpenCL in particular and parallel processing in general. IEEE Explore is their search engine, although usually all articles are also referenced in Google Scholar (but may be easier to find using IEEE explore).
ACM Digital Libray; ACM is a large and important institution like IEEE, but with even bigger focus on computing. You will find many papers on OpenCL there.
Google, Yahoo, Bing, etc; sometimes when everything else fails, using normal search engines can go a long way. You may find information about ongoing projects, important game developers blog posts, etc. All of these can be valid references if there aren't more (be sure to search really well before concluding there aren't more).
You should favor articles published in scientific journals over: a) papers or extended abstracts published in conference proceedings; b) corporate articles, not peer-reviewed, usually found in the respective corporation websites; c) articles published in general scientific knowledge magazines (e.g. Scientific American, etc.).
Sometimes you may not be given access to certain papers, which you will be requested to purchase. Usually, universities have subscriptions to many journals or such, as such you may have better luck trying to download the PDFs when accessing the web inside your institution. If you have no luck, sometimes the authors put "preview/unfinished" copies of the articles in their websites (sometimes they even put the dubiously legal published copy). As a last resort, you can always contact the authors directly, they'll most likely send you the article by email (it's of their own interest).
Finally, to learn OpenCL, I found that a mixture of reference manual, quick reference card and looking at examples from Intel, AMD, Nvidia and IBM SDK's goes a long way. No doubt a book will help, though I can't recommend you any, because I didn't read any.
This probably isn't the answer you wanted, but believe me, it's the answer you need to do a good work.
Good luck!
I am a software engineer working in Medical Imaging.I have just started using the language IDL and i feel very comfortable with it.As a new member in this field with a language like IDL, i would like to know the chances of IDL in this field.Can any one help me?
Well, so here is my biased opinion -> I'm heading the opposite way to you. I have used IDL (and before PV-Wave) on and off for ca 10 years (mostly MRI) and I'm now trying to part from it. Here is why. If you are proficient you can very quickly test something in an interactive / lightly scripted fashion. This is the typical use case of scientists; most have little CS education and are happy to grab any tool that seems to helpful. In fact, IDL is fairly good at dealing with largish arrays/images etc as you are likely to encounter in imaging.
However, it is not very pretty and coding gets increasingly awkward as your project size increases. If you are a software engineer, I suspect you'll hit the limits soon and will be cursing it no end. If you try to develop GUI code for people around you, you might be in for a rough ride. This is one of the main reasons I am moving over to Python + EPD with scipy and the likes. Also, binding to existing sophisticated image processing tools as you might need (registration, segmentation, etc) are not ideal.
A further complaint I have are the ongoing licensing costs. Even in an academic environment they are becoming prohibitive and I'd rather spend it on a Coop-student who could code for me than on ITT. A nice feature though is the ability to compile almost all IDL code into a sav file that others can use with a free IDL virtual machine.
Essentially, what it will come down to is how much your collaborators need you to use IDL. If it's fully your choice, I would look elsewhere. If there is a significant (and decent) code base, I would stay. The medical imaging plus astro community is dependent enough to keep this going for a while. If you do decide to hang on, I can highly recommend Dave Fanning's writings (his web page + his book + the google-group). He is somewhat of an icon in the idl community and certainly taught me things that were very useful. (Check out the mighty histogram function, I'm not kidding!)
Hope this works out for you.
I'm new to this field - but I need to perform a WAV-to-MIDI conversion in java.
Is there a way to know what exactly are the steps involved in WAV-to-MIDI conversion?
I have a very rough idea as in you need to;
sample the wav file, filter it, use FFT for spectral analysis, feature extraction and then write the extracted features on to MIDI.
But I cannot find solid sources or papers as in how to do all that?
Can some one give me clues as in how and where to start?
Are there any Open Source APIs available for this WAV-to-MIDI conversion process?
Advance thanks
It's a more involved process than you might imagine.
This research problem is often referred to as music transcription: the act of converting a low-level representation of music (e.g., waveform) into a higher-level representation such as MIDI or even sheet music.
The sophistication of your solution will depend upon the complexity of your input data. Tons of research papers address music transcription only on monophonic piano or drums... because they are easy to transcribe. (Relatively.) Violin is harder. Voice is even harder. Violin plus voice plus piano is much harder. A symphony is nearly impossible. You get the picture.
The basic elements of music transcription involve any of the following overlapping areas:
(multi)pitch estimation
instrument recognition, timbral modeling
rhythm detection
note onset/offset detection
form/structure modeling
Search for papers on "music transcription" on Google Scholar or from the ISMIR proceedings: http://www.ismir.net. If you are more interested in one of the above subtopics, I can point you further. Good luck.
EDIT: That being said, there are existing solutions that we can all find on the web. Feel free to try them. But as you do, evaluate them with a critical eye and ear. What types of audio signals would cause transcription to fail?
EDIT 2: Ah, you are only doing this for piano. Okay, this is doable. Music transcription has advanced to the point where it can transcribe monophonic piano pretty well. A Rachmaninov concerto will still pose problems.
Our recommendations depend upon your end goal. You state "need to perform... in Java." So it sounds like you just want something to work regardless of how it gets you there. In that case, I agree 100% with others: use something that exists.
That's actually an interesting question; all of the MIR libraries I know are typically C/C++/Python/Matlab. But not Java. The EchoNest has a Java API, but I don't think it does note-level transcription. http://developer.echonest.com. (Edit: It does note-level transcription. The returned data includes pitch, timbre, beat, tatum, and more. But I find polyphony is still a problem.)
Oh, Marsyas is Java-based. Cool. I thought it was just C++. http://marsyas.info/ I recommend this. It's developed by George Tzanetakis, a professor in MIR. It does signal-level analysis and should be a good option.
Now, if this is for a fun learning experience, I think you can use the sound manipulation utilities in Java to experiment with the WAV signal and see what comes out.
EDIT: This page describes MIR software better than I can: The Tools We Use
For Matlab, you may be interested in the MIR Toolbox
Here is a nice page of common datasets: MIR Datasets
This is a very big undertaking for being new to the field, unless you mean you are familiar with signal analysis and feature detection in general and want to look more specifically into automatic transcription.
There is no API for WAV to MIDI conversion. Vamp is a framework for feature extraction plugins, but to do automatic transcription you would need to use all the functionality of the existing plugins, plus implement functionality that exists in none of them yet.
Browse through the descriptions of the plugins on the vamp download page, any descriptions you do not understand are topics you should start researching if you want to do this.
If you don't need to automate this task (ie, for a website where people can upload MP3's and get MIDI files back), then you should consider using a tool like Melodyne which is already quite good at going this. As Steve noted, this is a very difficult task to accomplish, and even the best algorithms and solutions present at the moment are not 100% reliable.
So if you are just doing studio work and need to do a few conversions, it will probably save you a bit of time (and lots of headache) to use a tool already designed for this task.
This is a field which is still highly under development, yet, there are some (experimental) algorithms available.
You can install sonic annotator and use a few vamp plugins.
For example:
./sonic-annotator file.wav -d vamp:qm-vamp-plugins:qm-transcription:transcription -w midi
./sonic-annotator file.wav -d vamp:silvet:silvet:notes -w midi
./sonic-annotator file.wav -d vamp:ua-vamp-plugins:mf0ua:mf0ua -w midi
Dolphin, sorry to be brusque, but you have completely underestimated the problem. What you want to achieve - a full piano sound transcription involving all parameters that were used while playing would need an enormous amount of research with people who have worked in the field for many years. Even a group of PhDs in signal processing would have to invest a lot of work to even come close to what you mean. Music transcription has needed decades of work to even work halfway reliable. I'd suggest you pick a different problem which you can manage better than this.
Math skills are becoming more and more essential, and I wonder where is a good place to brush up on some basics before moving on to some more CompSci specific stuff?
A site with lots of video's as well as practice exercises would be a double win but I can't seem to find one.
It depends on your math level. You should start by revising what you should know till that moment and then go further to algorithm mathmatics, geometry (transforms and etc), statistics and more.
There are tons of places on the internet were you can learn:
http://www.math.cornell.edu/Courses/courses.html
http://ocw.mit.edu/OcwWeb/web/courses/courses/index.htm
http://mathworld.wolfram.com/
and the list is open.
I recommend Project Euler if you want to train number theory and discrete maths. Lots of fun exercises, though you need to know a bit of programming.
Steve Yegge had a good blog post Math for programmers
Quoting some of it:
"But a few things I've learned recently might surprise you:
Math is a lot easier to pick up after you know how to program. In fact, if you're a halfway decent programmer, you'll find it's almost a snap.
They teach math all wrong in school. Way, WAY wrong. If you teach yourself math the right way, you'll learn faster, remember it longer, and it'll be much more valuable to you as a programmer.
Knowing even a little of the right kinds of math can enable you do write some pretty interesting programs that would otherwise be too hard. In other words, math is something you can pick up a little at a time, whenever you have free time.
Nobody knows all of math, not even the best mathematicians. The field is constantly expanding, as people invent new formalisms to solve their own problems. And with any given math problem, just like in programming, there's more than one way to do it. You can pick the one you like best.
Math is... ummm, please don't tell anyone I said this; I'll never get invited to another party as long as I live. But math, well... I'd better whisper this, so listen up: (it's actually kinda fun.)"
I will be boring and recommend actually taking university courses in math.
Without lectures and lessons with an assistant I know I would never be able to learn as much as I have. I just need some kind of motivation, since higher math is really hard.
That is, if you are looking for quite advanced stuff and actually want to get a deep understanding and don't want to crunch numbers. Crunching numbers is why we have MATLAB ;)
It would be good to know what level of math you have, and what you want to do with it. But I guess calculus, linear algebra and discrete math are the most useful courses to take.
I suggest books with good tutorials throughout if you're unable to partake in a maths course. For computer science-related maths Don Knuth's Concrete Mathematics is meant to be very good.
Obviously nothing can replace a good teacher, but good tutorials can come pretty damn close. You really get to learn the subject in the tutorials I think.
Get some videos from www.aduni.org
Math courses
It's a couple of years since this question has been asked, but there are a number of new sites and resources available now:
Khan Academy was originally intended for schoolkids, but it has since expanded to include material that would not be out of place in first-year university courses. It serves as a great way to review and fix fundamentals. It has videos and practice exercises, and keeps track of your progress.
EdX is an evolution of initiatives like MIT Open Courseware. It's now an alliance of universities like MIT, Berkeley and Stanford that offer free online university level courses, with video instruction and learning materials. My only complaint is that some of their courses have prerequisites (like single-variable calculus) that you need to pick up elsewhere, like Coursera, or the original MIT OpenCourseWare site.
Coursera offers more courses than EdX, and many of them are more basic, covering topics like pre-algebra and pre-calculus. The learning interface is not quite as cool as EdX's (which offers a scrollable captioning interface alongside most of it's videos), but the broader range of topics and courses covering fundamentals offers learning you just won't find on EdX.
A lot of the universities will actually publish their lecture materials online. So all you really need to do is find a suitable subject and then read the lecture materials and do the associated work. If you were really sneaky you could probably also go to the tutorials to get help :P
BetterExplained.com has some great math lectures. Its not video lectures but the author gives easy-to-understand explanations on math concepts.
Don't forget that iTunes now has available a load of maths lectures (and other subjects) from various mainstream universities - and all for free.
Since you want to brush up your math
I would suggest you to do a G search on UCCS math online
Or follow this link , and after registering yourself free you can browse the archives
I must say that It's common that you will find people recommending course X .
But rarely will you find people completing their recommended course ..
SO IN the case of number theory you must go for the latest course , the last offering has not high quality video ..
Also for Discrete Math ->There are no lecture notes on this site
So you have to figure out how to establish correspondence two online course (6.042 has good P sets and Notes) And The above Math course for Discrete Math .
I would discourage you to use YouTube (x minutes ) tutorials , Because most of them cover Math like History ..
A good course can be found by G searching Harvard OlI--
It has probability (Non Continuous) - There are P sets without solutions ..