EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding
Table 2: Comparisons of decoding speed between the phoneme-based Eesen system and the hybrid HMM/DNN system. “RTF” refers to the real-time factor in decoding. “Graph Size” means the size of the decoding graph in terms of megabytes.
['Model', 'RTF', 'Graph Size']
A major advantage of Eesen compared with the hybrid approach is the decoding speed. The acceleration comes from the drastic reduction of the number of states, i.e., from thousands of senones to tens of phonemes/characters. From their real-time factors, we observe that decoding in Eesen is 3.2× faster than that of HMM/DNN. Also, the decoding graph (TLG) in Eesen is significantly smaller than the graph (HCLG) used by HMM/DNN, which saves the disk space for storing the graphs.