Markus Toman

Artificial Intelligence, Speech Technology and Software Development

Artificial intelligence in speech synthesis

(Dear international readers, this content appeared first in the German “IT Freelancer Magazin” and is unfortunately only available in German)

Es war Anfang 2012 als ich mich für ein Doktorat im Bereich Sprachsynthese bewarb. Ehrlich gesagt konnte ich mir damals nicht viel darunter vorstellen, aber die Ausschreibung beinhaltete Machine Learning und Künstliche Intelligenz. Und es klang irgendwie… anders. Heute – über 5 Jahre später – habe ich einen ganz guten Überblick über das Thema, stoße aber im Gespräch mit anderen Menschen stets auf das selbe Unverständnis, das ich damals aufwies. Dieser Artikel soll nun in groben Zügen und allgemeinverständlich die Aufgabenstellung und Probleme moderner Sprachsynthese aufzeigen.

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Examples for performance optimization in C and C++, Part 2

This is part 2 of “Examples for performance optimization in C and C++”, you can find part 1 here: Examples for performance optimization in C and C++, Part 1

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Examples for performance optimization in C and C++, Part 1

This brief case report shows an example for performance gains that can be achieved in C and C++ by simple analysis and code restructuring. It does not describe performance optimization in detail.

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Importing DNN weights in tiny-DNN

tiny-dnn is a C++11 implementation of deep learning. It is suitable for deep learning on limited computational resource, embedded systems and IoT devices.”

https://github.com/tiny-dnn/tiny-dnn

 

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Some hints for working with the Apple Audio Queue Services

I’ve recently been implementing the Speech Synthesis SDK on iOS at VocaliD and wanted so share some quick hints on working with the Apple Audio Queue Services. This is no thorough treatise but just a few bullets points that might be helpful.

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A 90s teenage tale of programming and nerd culture

I’ve recently been reading the article “Coding needs a new youth movement” in which the author proposes that beginner programming courses should focus on “frontend” technologies to motivate students. Instead of “backend” technologies like Java, that is. This lead me to take a look back at the time when I wrote my first lines of code, which was more than 20 years ago. I assume that many creators of said programming courses also started at least back then, probably being the reason why the courses are structured in the way the are.

In the beginning of the 90s, there was no notion of “frontend” vs. “backend” developers, only programmers. Of course there was user interface design, but that’s a different beast. Java just crawled out of the womb, same with JavaScript, so programming usually meant picking up e.g. Assembler, C, C++, Pascal or COBOL. Web development also just began to rear its ugly head and usually meant having some CGI producing HTML.  I doubt that seeing some colorful webpages (<blink/>) with some buttons and text fields would have brought me to programming back then. But writing Fibonacci generators most likely neither.

So here I would like to share (the beginning of) my journey from interested kid to CS PhD. This might end up as some sort of boring, archaeological curiosity but I still hope I can share at least some funny stories, pictures and lots of links (you notice all the highlighted words, right?).

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