# Tibetan Speech Synthesis Based on Pre-Trained Mixture Alignment FastSpeech2
## 3 Experiments and Results
### Evaluation Indicators and Experimental Results
#### 3.5.2 Subjective Evaluation Results  
Subjectively, ten Tibetan texts were randomly selected to compare the speech synthesis effects of FastSpeech2 and Mixture Alignment FastSpeech2. Furthermore, experiments utilized pre-trained models on the LJSpeech dataset. Subsequently, five Tibetan participants rated the synthesized speech using different models. The MOS was then calculated, and results are displayed in Table 3. In the first row of the table, \"Ground Truth\" refers to the original recordings of the selected Tibetan texts used as a reference for evaluating the quality of synthesized speech.  
To assess the effectiveness of the speech synthesis models, we first conducted an analysis of variance (ANOVA) to determine if there were any statistically significant differences among the mean opinion scores (MOS) of the various models. The ANOVA results revealed a significant overall difference (F-value = 11.90, \(p<0.001\)), indicating that at least one of the models differed significantly from the others.  
To further investigate which specific pairs of models exhibited significant differences, we performed a post-hoc Tukey HSD test. The results of this test are summarized in Table 4. The table shows the adjusted \(p\)-values for comparisons between each model and the mixture alignment FastSpeech2+ pre-trained model.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Voice Quality** & **MOS Evaluation Criteria** & **Grading Value** \\ \hline Very Good & Clear voice, smooth communication, and low latency & 5 \\ Good & Voice is clearer but communication is a bit difficult & 4 \\  & with murmurs & \\ Medium & The voice is not very clear, but communication is possible & 3 \\  & with a slight delay & 2 \\ Bad & Unclear sound, requires multiple repetitions to communicate, & \\  & and has high latency & 2 \\ Very Bad & Completely unintelligible and very difficult to communicate & 1 \\  & with a large delay & 1 \\ \hline \hline \end{tabular}
\end{table}
Table 2: MOS Scoring Criteria.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Model** & **MOS** \\ \hline Ground truth & 4.52 \(\pm\) 0.09 \\ FastSpeech2 & 3.65 \(\pm\) 0.08 \\ FastSpeech2+ pre-trained model & 3.71 \(\pm\) 0.08 \\ Mixture alignment FastSpeech2 & 3.76 \(\pm\) 0.07 \\ Mixture alignment FastSpeech2+ Pre-trained model & 3.82 \(\pm\) 0.09 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Subjective evaluation results.  
The Tukey HSD test revealed that the mixture alignment FastSpeech2+ pre-trained model showed a significant improvement over both FastSpeech2 (\(p\) = 0.0065) and the FastSpeech2+ pre-trained model (\(p\) = 0.0065), confirming its superior performance.  
Following the ANOVA, we performed a post-hoc Tukey HSD test to identify which specific pairs of models exhibited significant differences. The Tukey HSD results are summarized as follows: the mixture alignment FastSpeech2+ pre-trained model demonstrated a significant improvement over both FastSpeech2 (\(p\) = 0.0065) and the FastSpeech2+ pre-trained model (\(p\) = 0.0065), confirming its superior performance.