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It is not easy to detect East Asia's presence in the field of investor-state dispute settlement (ISDS), despite its large economy. In addition to having less active foreign direct investment (FDI) relative to GDP and fewer investment treaties, East Asian economies and societies seem to possess certain characteristics that have contributed collectively to the dearth of ISDS cases in East Asia. Examples are the short history of international arbitration, the avoidance of litigation, the high proportion of state-owned enterprises in outward FDI from China, and the concentration of FDI in industries in which investor-state disputes are less likely to occur. This trend, however, is likely to change gradually with the ongoing socioeconomic changes in the region, including the increase in both outward and inward FDI, the increasing number of investment treaties, the growing familiarity with international (investment) arbitration among legal experts, the diversification of FDI, and the decreasing fear of administrative litigation.

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While Current TTS systems perform well in synthesizing highquality speech, producing highly expressive speech remains a challenge. Emphasis, as a critical factor in determining the expressiveness of speech, has attracted more attention nowadays. Previous works usually enhance the emphasis by adding intermediate features, but they can not guarantee the overall expressiveness of the speech. To resolve this matter, we propose Emphatic Expressive TTS (EE-TTS), which leverages multi-level linguistic information from syntax and semantics. EE-TTS contains an emphasis predictor that can identify appropriate emphasis positions from text and a conditioned acoustic model to synthesize expressive speech with emphasis and linguistic information. Experimental results indicate that EE-TTS outperforms baseline with MOS improvements of 0.49 and 0.67 in expressiveness and naturalness. EE-TTS also shows strong generalization across different datasets according to AB test results.

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