Using the speech recognition virtual kitchen infrastructure for reproducible cross-disciplinary speech research exchange

Computational models and methods of analysis have become a mainstay in speech research over the last seventy years, but the means for sharing software systems is often left to personal communication between model developers. As a result, the sharing of systems is typically complicated, error-prone, or simply not done at all, making it difficult (in some cases impossible) to verify model performance, engage with developers directly using their own models, or bridge gaps between research communities that have diverged over time. Moreover, the learning curve for new students or tech consumers entering these communities is quite steep, limiting the use of the models to those initiated in a given area. Over the last few years a number of computing infrastructures have taken shape that aim to address the difficulties encountered in the exchange of large software systems (e.g., the Berkeley Computational Environment, http://collaboratool.berkeley.edu/). We present the Speech Recognition Virtual Kitchen (www.spee...