## 4 Results  
After analyzing the various samples to calculate error rates related to automatic speech-recognition analysis, such as the WER [40], we proceed to compute various statistics, such as the mean, median, standard deviation, and variance. Additionally, we calculated the 95% confidence intervals to ensure that the results obtained were conclusive. A preprocessing step was performed on the character strings to obtain a WER that is as realistic as possible. This involved removing punctuation marks, exclamation marks, question marks, etc., and converting all strings to lowercase. This ensured that the WER calculation would not be affected by different interpretations between Alexa and Whisper beyond the simple transcription of the words heard. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Accent** & **Alexa** & **Whisper Base** &
\begin{tabular}{l} **Whisper** \\ **Large-v2** \\ \end{tabular} \\ \hline Andean & 2016 & 2016 & 2016 \\ Canary & 562 & 562 & 562 \\ Caribbean & 1537 & 1537 & 1537 \\ Central American & 1501 & 1501 & 1501 \\ Chilean & 1268 & 1268 & 1268 \\ Spain Central & 1958 & 1958 & 1958 \\ Spain Northern & 2150 & 3610 & 3610 \\ Spain Southern & 1456 & 1456 & 1456 \\ Mexican & 2150 & 34,639 & 11,600 \\ Rioplatense & 2150 & 2914 & 2915 \\ \hline Total & 16,748 & 51,461 & 28,423 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Sample sizes used for females. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Accent** & **Alexa** & \
\begin{tabular}{l} **Whisper** \\ **Base** \\ \end{tabular} &
\begin{tabular}{l} **Whisper** \\ **Large-v2** \\ \end{tabular} \\ \hline Andean & 2150 & 11,493 & 11,493 \\ \hline Canary & 1482 & 1482 & 1482 \\ \hline Caribbean & 2150 & 6041 & 6041 \\ \hline Central American & 2150 & 3908 & 3908 \\ \hline Chilean & 2150 & 3939 & 3939 \\ \hline Spain Central & 2150 & 6930 & 6930 \\ \hline Spain Northern & 2150 & 31,406 & 11,600 \\ \hline Spain Southern & 2150 & 30,698 & 11,600 \\ \hline Mexican & 2150 & 47,020 & 11,600 \\ \hline Rioplatense & 2150 & 8359 & 8359 \\ \hline Total & 20,832 & 151,276 & 76,952 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Sample sizes used for males. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Accent** & **Mean** & **Median** & **Stdev** & **Variance** & **CI 95\%** \\ \hline Andean & 25.72 & 15.38 & 38.38 & 14.73 & 1.68 \\ Canary & 18.08 & 10.00 & 25.23 & 6.37 & 2.09 \\ Caribbean & 26.05 & 16.67 & 32.66 & 10.66 & 1.63 \\ Central American & 22.34 & 14.29 & 27.39 & 7.50 & 1.39 \\ Chilean & 24.71 & 16.67 & 35.61 & 12.68 & 1.96 \\ Spain Central & 20.85 & 12.50 & 39.46 & 15.57 & 1.75 \\ Spain Northern & 21.69 & 14.29 & 32.98 & 10.87 & 1.08 \\ Spain Southern & 25.52 & 16.67 & 33.79 & 11.42 & 1.74 \\ Mexican & 25.67 & 18.18 & 30.81 & 9.49 & 0.32 \\ Rioplatense & 21.18 & 14.29 & 38.43 & 14.77 & 1.40 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: WER (%): Whisper (Base), Male. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Accent** & **Mean** & **Median** & **Stdev** & **Variance** & **CI 95\%** \\ \hline Andean & 22.71 & 14.29 & 53.11 & 28.21 & 0.97 \\ Canary & 21.78 & 16.67 & 23.24 & 5.40 & 1.18 \\ Caribbean & 26.46 & 16.67 & 37.24 & 13.87 & 0.94 \\ Central American & 20.70 & 14.29 & 28.99 & 8.40 & 0.91 \\ Chilean & 21.06 & 14.29 & 27.09 & 7.34 & 0.85 \\ Spain Central & 21.02 & 14.29 & 27.77 & 7.71 & 0.65 \\ Spain Northern & 17.95 & 10.00 & 37.28 & 13.90 & 0.41 \\ Spain Southern & 64.10 & 57.14 & 63.37 & 40.16 & 0.71 \\ Mexican & 26.35 & 16.67 & 45.14 & 20.37 & 0.41 \\ Rioplatense & 20.75 & 14.29 & 26.95 & 7.26 & 0.58 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: WER (%): Whisper (Base), Female. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Accent** & **Mean** & **Median** & **Stdev** & **Variance** & **CI 95\%** \\ \hline Andean & 44.06 & 28.57 & 39.53 & 15.62 & 1.73 \\ Canary & 51.19 & 39.23 & 42.14 & 17.76 & 3.49 \\ Caribbean & 49.33 & 37.50 & 40.39 & 16.31 & 2. Table 14 displays the gender differences for each variant of Alexa and Whisper analyzed by weighted means of WER.