# Auditory Perception of Impulsiveness and Tonality in Vocal Fry
## 4 Discussion
Most of the scientific attention on physical voice synthesis had gone in the past into the physical synthesis of voices with higher frequencies, which results in a lack of understanding synthesis of low-frequency voices. In addition, we had expected that the use of a small open quotient of approximately 0.1 to 0.3 would be necessary at frequencies from 20 Hz to 30 Hz to produce naturally sounding stimuli because the duration of the open phase at such frequencies is short compared withthe cycle duration. This expectation was not confirmed, because we did not see such an effect in the naturalness ratings. We also saw that perceived naturalness increased slightly as the individual experiments progressed, which is interpreted as the listeners becoming familiar with the sounds of the stimuli. Fourth, we observed that the use of a majority vote in place of individual listeners' ratings yields a better agreement between ratings and LPP. For Experiment 1, the AUC increased to 0.98 using a threshold of 0.14 sone, and the AUC of Experiment 2 increased to 0.90 with a threshold of 0.07 sone when a majority vote was used. This observation may be interpreted in terms of the presence of noise in the responses of individual listeners, which is canceled out in majority voting. Therefore, binary fry labels obtained via majority voting as well as cutoff thresholding of the LPP may be closer to the actual truth than ratings of individual listeners. The same interpretation may be applied to the observation that the prediction of perceived binary fry from perceived impulsiveness improves if a majority vote is used instead of ratings of individual listeners. Fifth, regarding the internal reference standards of the listeners, we found indications for the existence of fixed components of reference standards, as well as for effects of anchoring and for the influence of short-term context on listener ratings. Regarding fixed standards, we found that two listeners were not susceptible to anchoring. They were both medical doctors, which suggests a professional group effect. However, for a third medical doctor the 50% probability threshold of 74 Hz agrees with the all-listener mean threshold (see Figure 6). Regarding anchoring, most of the listeners appeared to be susceptible. In particular, we found differences between the ratings obtained in Experiments 1 and 2, which we interpret as a result of differences in anchoring. Regarding effects of the short-term context, we found significant effects of \(\Delta\)Fo on 7-point Likert ratings of tonality, impulsiveness, and naturalness. The effect of \(\Delta\)Fo was marginally non-significant on perceived binary fry. Finally, the heterogeneous backgrounds of the listeners has the drawback of generating small group sizes for individual professions. An advantage of diverse backgrounds, however, is that the inclusion of listeners with different professional backgrounds reflects the range of possible listener behaviors in the data. In addition, the language that we used for the labels in the GUI was English, which was the second language for all listeners. (The first languages were German, Luxembourgish, and Telugu). Listeners were familiarized with the English semantic descriptors in the GUI prior to the experiment in a short conversation with author [PERSON]. The limitations of the study and suggestions for future research include the following. First, the low-frequency signals were labeled as less natural. The synthesizer is able to produce stimuli that are indistinguishable from human stimuli [41], but no arbitrary setting of the synthesizer parameters is guaranteed to produce natural speech sounds. This highlights the difficulty of synthesizing vocal fry signals that sound convincingly human. For the future, we consider the possibility of synthesizing fry signals with neural network-based approaches (e.g., WaveNet, or WaveGlow [42; 43]) and conducting Turing tests to assess the naturalness of their outputs.