OpenSTT is An exploration of end-to-end automatic speech recognition systems (ASR) for the largest open-source Russian language data set. It evaluate different existing end-to-end approaches such as joint CTC/Attention, RNN-Transducer, and Transformer. All of them are compared with the strong hybrid ASR system based on LF-MMI TDNN-F acoustic model.For the three available validation sets (phone calls, YouTube, and books),best end-to-end model achieves word error rate (WER) of 34.8%,19.1%, and 18.1%, respectively. Under the same conditions, the hybridASR system demonstrates 33.5%, 20.9%, and 18.6% WER.
License：CC-BY-NC and commercial usage available after agreement with dataset authors.