The IARPA Babel program developed speech recognition technology for noisy telephone conversations.
The main goal of the program was to improve the performance of keyword search on languages with very little transcribed data, i.e. low-resource languages.
[1] Beginning in 2012, two industry-led teams (IBM and BBN) and two university-led teams (ICSI led by Nelson Morgan and CMU) participated.
Only BBN[3] and IBM[4][5][6] made it to the final evaluation campaign in 2016, in which BBN won by achieving the highest keyword search accuracy on the evaluation language.
Some of the funding from Babel was used to further develop the Kaldi toolkit.