# Gated Recurrent Attention for Multi-Style Speech Synthesis
## 5 Conclusions  
We proposed and evaluated the Gated Recurrent Attention, a novel attention mechanism with gated recurrence for enriching style modeling capability in multi-style speech synthesis. Although the GRA is not a technique for directly modeling style such as global style tokens, the experimental results show that the GRA can improve the similarity and naturalness of synthesized speech. GRA was found to be more effective in transferring unseen styles, which implies that the generalization performance \begin{table}
\begin{tabular}{l c} \hline \hline \multicolumn{1}{c}{(**a**) CCR} \\
**Similarity** & **Score** \\ \hline GRA is much more similar & 3 \\ GRA is more similar & 2 \\ GRA is slightly more similar & 1 \\ About the same & 0 \\ LSA is slightly more similar & \(-1\) \\ LSA is more similar & \(-2\) \\ LSA is much more similar & \(-3\) \\ \hline \multicolumn{1}{c}{(**b**) ACR} \\
**Quality** & **Score** \\ \hline Excellent & 5 \\ Good & 4 \\ Fair & 3 \\ Poor & 2 \\ Bad & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: (**a**) Comparison category rating CCR method for similarity comparison mean opinion score (CMOS) and (**b**) absolute category rating (ACR) method for naturalness mean opinion score (MOS). \begin{table}
\begin{tabular}{l c c c} \hline \hline \multicolumn{1}{c}{**Speaker of**} & \multicolumn{2}{c}{**CMOS**} & \multicolumn{2}{c}{**MOS**} \\
**Reference Audios** & & **LSA** & **GRA** \\ \hline MAILABS\_[PERSON] & 0.447 \(\pm\) 0.110 & 3.133 \(\pm\) 0.085 & **3.303 \(\pm\) 0.080** \\ MAILABS\_[PERSON] & 0.096 \(\pm\) 0.114 & **4.113 \(\pm\) 0.065** & 4.100 \(\pm\) 0.078 \\ MAILABS\_[PERSON] & 0.438 \(\pm\) 0.120 & 3.793 \(\pm\) 0.089 & **4.213 \(\pm\) 0.069** \\ \hline MAILABS\_average & 0.327 \(\pm\) 0.067 & 3.680 \(\pm\) 0.051 & **3.872 \(\pm\) 0.048** \\ \hline VCTK\_p226 & 0.828 \(\pm\) 0.191 & 2.953 \(\pm\) 0.158 & **3.313 \(\pm\) 0.147** \\ VCTK\_p248 & 1.172 \(\pm\) 0.197 & 2.594 \(\pm\) 0.156 & **3.578 \(\pm\) 0.192** \\ VCTK\_p255 & 0.453 \(\pm\) 0.175 & 2.594 \(\pm\) 0.172 & **2.672 \(\pm\) 0.157** \\ VCTK\_p270 & 0.227 \(\pm\) 0.214 & **3.086 \(\pm\) 0.151** & 2.961 \(\pm\) 0.163 \\ VCTK\_p282 & 0.906 \(\pm\) 0.196 & 2.484 \(\pm\) 0.160 & **3.242 \(\pm\) 0.194** \\ VCTK\_p293 & 0.719 \(\pm\) 0.264 & 3.938 \(\pm\) 0.169 & **4.188 \(\pm\) 0.132** \\ VCTK\_p295 & 0.102 \(\pm\) 0.223 & 3.969 \(\pm\) 0.175 & **4.266 \(\pm\) 0.126** \\ VCTK\_p299 & 0.219 \(\pm\) 0.206 & 4.047 \(\pm\) 0.171 & **4.125 \(\pm\) 0.154** \\ VCTK\_p306 & 0.781 \(\pm\) 0.254 & 3.789 \(\pm\) 0.171 & **4.313 \(\pm\) 0.130** \\ VCTK\_p334 & 0.086 \(\pm\) 0.161 & 2.641 \(\pm\) 0.152 & **2.648 \(\pm\) 0.147** \\ VCTK\_p360 & 0.055 \(\pm\) 0.214 & **3.070 \(\pm\) 0.157** & 3.055 \(\pm\) 0.154 \\ VCTK\_p376 & 0.930 \(\pm\) 0.182 & 2.930 \(\pm\) 0.146 & **3.039 \(\pm\) 0.153** \\ \hline VCTK\_average & 0.540 \(\pm\) 0.063 & 3.174 \(\pm\) 0.055 & **3.450 \(\pm\) 0.054** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Similarity CMOS and naturalness MOS. of GRA is better than that of conventional techniques. Other gating architectures such as LSTM can be easily applied to the GRA. If a prominent gate-based RNN is introduced, the effect of the GRA may be boosted by it. As the GRA is a general attention method that can be applied to any sequential process, GRA can be evaluated on time series data or video processing in further studies. Conceptualization, S.J.C. and N.S.K. ; methodology, S.J.C. and J.Y.L. ; software, S.J.C. and H.L. ; validation, S.J.C. and N.S.K. ; formal analysis, S.J.C. ; investigation, S.J.C. and B.J.C. ; resources, S.J.C. and N.S.K. ; data curation, S.J.C. ; writing--original draft preparation, S.J.C. ; writing--review and editing, J.Y.L., B.J.C., H.L., and N.S.K. ; visualization, S.J.C. ; supervision, N.S.K. ; project administration, N.S.K. ; funding acquisition, N.S.K. All authors have read and agreed to the published version of the manuscript.