# Interaural Coherence Estimation for Speech Processing in Reverberant Environment
## 5 Conclusions  
This paper proposed an IC estimation method that applies the exponential weight with \(\beta\) to \(L_{\text{T}}\) time-frequency bins of the same length as the quasi-steady interval of speech and mean accuracy of coherence (MAC) to quantify estimation performance. The optimal \(L_{\text{T}}\) and \(\beta\) according to gender, frequency, and reverberation time were determined, but the results showed that gender does not affect optimal parameters. The speech characteristics change according to age and language; thus, the effects of age and language especially in correlation with their spectrograms need to be investigated. The optimal \(L_{\text{T}}\) and \(\beta\) values were determined as the maximum point of the histogram with MACtotal in specific reverberation environments with 0.37 s, 0.69 s, and 0.79 s of RT60. The optimal parameters for only specific reverberation environments were proposed in this paper. However, based on the theoretical analysis and the tendency of the numerical experiment results, the optimal parameters in any reverberation environment can be determined as \(L_{\text{T}}\) and \(\beta\) with small values at high frequency and low reverberation time. The IC estimation of reverberant speech with STFT variables, which are mainly used for speech processing, using the proposed method with optimal parameters showed 0.0008, 0.0255, and 0.0524 larger MACtotal than the conventional method; thus, the proposed method achieved better estimation performance. While the conventional method is in the form of an IIR filter, the proposed method is in the form of an FIR filter; therefore, it provides the accurate IC with less distortion of the estimated PSD and less computation time. However, the FIR filter needs more coefficients and, therefore, it may require more computations than the IIR filter. In the simulations, the difference in IC estimation performance was small, but intensive improvement was found in the vicinities of the border between direct and diffused speech, which implies that the proposed method has advantage in the rapid change of speech data because past data do not affect current PSDs in the FIR filter. On the other hand, the estimation performance for diffuse speech was degraded compared to the conventional method. Some diffuse speech bins have lower energy than direct speech bins. Since the importance of the coherence estimation accuracy for these bins is small, the proposed method that estimates direct speech more accurately is more suitable.  
Conceptualization, S.-H.K. and Y.-H.P.; methodology, S.-H.K.; software, S.-H.K.; validation, S.-H.K.; formal analysis, S.-H.K.; investigation, S.-H.K.; resources, S.-H.K.; data curation, S.-H.K.; writing--original draft preparation, S.-H.K.; writing--review and editing, S.-H.K. and Y.-H.P.; visualization, S.-H.K.; supervision, Y.-H.P.; project administration, Y.-H.P.; funding acquisition, Y.-H.P. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
This research was supported by the \"Human Resources Program in Energy Technology\" of the Korea Institute of Energy Technology Evaluation and Planning (KETEP), the Ministry of Trade, Industry & Energy, Korea (No. 20184030202000), and the \"Research Project for Railway Technology\" of the Korea Agency for Infrastructure Technology Advancement (KAIA).  
The authors declare no conflicts of interest.