There's no shortage of FOSS software for automatic speech recognition. Most academic research these days uses the Kaldi toolkit (http://kaldi.sourceforge.net/ab

There's no shortage of FOSS software for automatic speech recognition. Most academic research these days uses the Kaldi toolkit (http://kaldi.sourceforge.net/about.html http://kaldi.sourceforge.net/about.html), which has an Apache license. There are (at least) three problems that prevent the widespread availability of FOSS speech recognizers: 1. Data. Large corpora are available via Penn's Linguistic Data Consortium (LDC). Big academic institutions can afford their all-inclusive licenses; small corporations have to settle for their expensive a la carte options, and startups and hobbyists have to go without. Fortunately, there is now more and more freely available data, such as the LibriSpeech database (http://www.voxforge.org/home/forums/message-boards/audio-discussions/librispeech-corpus-is-available http://www.voxforge.org/home/forums/message-boards/audio-dis...), which is extracted from the LibriVox website (of public-domain audiobooks). 2. Task-specificity. Speech recognition systems need extensive customization to the intended use case to achieve good performance. Conventional wisdom is that your recognizer can be tuned to work with a wide variety of speakers, or support a large vocabulary, but not both. This customization requires lots of time, data, and expertise. 3. Expertise. Speech recognition development is a PhD-level activity. After 5 years of stable or declining real income, smart students either go work for big bucks at a large multinational, or can't get a visa and go back to their home country. While there's some hope for #1, #2 and #3 aren't going away anytime soon.