== The speech decoder ==
* Decoder** Third-party licensing is extremely costly (usual unit is millions) and lead to an unwanted dependency. Write a decoder from scratch is tough, and requires highly specialized and difficult to find engineers.
The good news are that exists great open source toolkits that we can use and enhance. I am a long time supportert and contributor of CMU Sphinx that have a number of quality models on different languages openly available. Plus pocketsphinx can run very fast and accurate when well tuned for both FSG and LVSCR language models.
* Automatic retrain
** We should also build scripts to automatically adapt the acoustic model per user with his own voice, to constantly auto-improve the service individually for him but also for the service as overall.
* Privacy
** Some argued with me about privacy on online services. At the ideal screnario, actually online recognition is required only for LVSCR, while FSG can be handled offline if architected correctly. I think letting users to choose or not to let us use his voice to improve models is how other OSes handle this issue.
* Offline and online
** The same speech server can be designed to run both online as offline, letting the responsibility to handle transmission to the middleware that handle the connections with the front.
== Web Speech API ==
