For Latvian and Lithuanian languages the situation is better, for example, there are a 100h Lithuanian speech corpus created for the LIEPA project 1 , an 84h corpus from BMMG (Alumäe and Tilk, 2016) and a 100h Latvian speech corpus (Pinnis et al., 2014).
even this is not much, as neural network acoustic models can make use of many thousands of hours of data and achieve significant improvement in recognition accuracy.