The goal of the study is to compare the recognition of four emotions “joy-neutral-sadness-anger” in different types of child’s speech across two languages: Russian and Tamil. The participants of the study were 8-12 year-old children: 12 Russian speaking children (born and living in St. Petersburg, Russia) and 18 Tamil speaking children (born and living in Vellore, India); 26 adults – listeners by 13 native speakers of the Russian and Tamil languages. The speech materials were spontaneous speech and “acting” speech. It is shown that Russian and Indian experts are capable to recognize correctly the emotional states of children by their speech, but with varying accuracy. The native Russian and Tamil speaking experts were more accurate in recognizing the emotional states of children in their native language, in the “acting” speech vs. spontaneous speech. The data of the cross-cultural study support the view that emotional speech includes universal and culture–specific features.
In underwater wireless optical communication (UWOC) systems, scattering and absorption occur due to water molecules and suspended particles, resulting in weak signals at the receiver end. In this study, we employed a low-density parity-check (LDPC) code, which is a kind of error-correcting code, in order to compensate for performance loss, and its performance was improved only when the input values of the decoder were soft decision types. However, no algorithm has yet been reported that applies a soft decision technique for the M-ary pulse position modulation (PPM) and quadrature amplitude modulation (QAM) schemes in the case of UWOC. Therefore, we developed a soft value generator (SVG) algorithm in order to use a turbo equalizer, which improves the performance over all of the iterations in the case of the M-ary PPM and QAM schemes. Through simulations, we confirmed that the proposed method performs better than the conventional hard decision algorithm. We also evaluated the performance of the proposed method through water tank experiments, in which M-ary PPM and QAM data were employed to perform experiments by varying the turbidity and transmission rates in a water tank. This again showed that the performance of the proposed algorithm is superior to that of the conventional algorithm.