Modern ASR practices review

I was never able to completely join the scientific world, most probably because engineering tasks are more attractive. Though I graduated as a mathematician, my merits aren't worth mentioning. For example the thing I never liked is writing, in particular writing a scientific article. That's the corner stone of the science now but for me it seems very dated practice. Most articles are never read, huge percent has errors, many are completely wrong or repeat other sources. Of course there are brilliant ones.

From my point of view the knowledge should be probably organized in a different ways, something like a software projects. The theory could be built during ages in a wiki style with all changes tracked and probably contain complimentary information like techinical notes, software implementations, test results, formalized proofs and so on. Of course among software projects there are also issues like forks, bad maintaince and bugs, but it seems they are more organized.

That's why I really like the projects that keep knowledge in a structure like wikipedia, planetmath for example. Also reviews of the state of art are of course invaluable. Today I spent some time processing my library and the found again the wonderful review by Mark Gales:

The Application of Hidden Markov Models in Speech Recognition

I would really recommend this book as a base introduction into modern speech recognition methods. Though written by HTK author, it has little HTK specific and really focused in best practices in ASR systems.

P.S. Is there a personal library management software, web-based, able to store and index PDF? I used to install Dspace at work, but it's so heavy and the UI is really outdated.

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