## 5 Conclusions  
In this work, the SVD database was used, since it presents voice signals of sustained vowels and speech signals of a sentence, which are the required conditions for the type of analysis intended. An algorithm was developed to determine the HNR, the Autocorrelation, and the NHR. The algorithm uses an integer number of glottal periods to determine the frame to be analyzed, so it was necessary to compare the algorithm values and the reference values. The selection of windows and their length were optimized. One of the analyses was to search for the best window contour and length so that the value of the parameters was as close as possible to the reference value. For the HNR parameter, the patient subjects' samples obtained the lower difference using a Hanning window with six glottal cycles, and for normophonic voices, the Hanning or Blackman window, both with six glottal cycles. In the comparative analysis between subjects, it is possible to perceive that the values of HNR of the algorithm and reference software are pretty close. Therefore, considering both groups of subjects, a Hanning window with six glottal cycles was selected. For the Autocorrelation, the objective is also to know the best window and length to obtain, through the algorithm, the value for this parameter as close as possible to the reference value. Thus, through the analysis made for the Autocorrelation, the three windows (Hamming, Hanning, and Blackman) with six glottal cycles obtain the lower difference. However, the Hanning window with six glottal cycles will be considered because, as seen in the flowchart of Figure 3, it allows the processing of Autocorrelation and HNR simultaneously, reducing the computational load. In the comparative analysis between subjects, it is possible to observe that the results obtained by the algorithm and the reference for Autocorrelation are practically identical for patient and control subjects. The window and its length were not analyzed extensively for the NHR since it was completed for Autocorrelation, thus justifying the choice of window and length. However, the comparative analysis of NHR between subjects was performed, and the results obtained by the algorithm and the reference are practically identical for both cases (patients and control). A further analysis was made to see if the variation of the sampling frequency influences the Autocorrelation and HNR values. The decimation was made for the same speech samples to have signals with a sampling frequency of 12.5 kHz and 25 kHz. For HNR, the values of the algorithm vary with the sampling frequency and have a maximum variation of 2.04 dB. Further analysis showed that the variations occur mainly in the measurements with a sampling frequency of 12.5 kHz for all vowels and tones. For the Autocorrelation, the variation of the sampling frequency is insignificant since the Autocorrelation difference is 0.001 and 0.004, comparing the algorithm values with the reference values. Therefore, the sampling frequency does not significantly influence the Autocorrelation value. In the analysis of the HNR and the Autocorrelation measurements on the generated signal, it was noticed that the algorithm and the reference software measured the same. A comparative analysis with the USP database was made. The same mean absolute difference level was noticed on Autocorrelation measurements, and a slight increase on HNR mean absolute difference. As a final consideration, the proposed efficient algorithm allows the determination of the short-term Autocorrelation, HNR, and NHR using a Hanning window with six glottal periods length without overlapping with results very close to the ones presented by Praat software. The algorithm gives similar measurements at 50 kHz sampling frequency and 25 kHz. The average absolute difference is lower than 0.004 for the Autocorrelation and 0.42 dB for HNR. Future research on the issue is to use the algorithm in a smart support system for vocal analysis, which is already under development. Conceptualization, J.F.T.F. and J.P.T.