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Exploring the Factors Aiding Speech-to-Text Emotional Restoration

机译:言语文本情感恢复的辅助因素探析

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摘要

In recent years, with the development of artificial intelligence technology, speech recognition technology can perform high-precision interpretation and transcription on voices in various complex environments, improving typing efficiency. However, the text obtained by speech translation is only composed of text and simple punctuation, which hinders the real emotion expression of users. The pale translated text hinders the formation of context, affects the emotional transmission of semantics, and lead to a poor user experience when users communicate with others. Based on user experience and emotion, this article discusses the factors that assist the speech-to-text emotional restoration. Through the qualitative and quantitative study, this research compares four emotional effects of information texts composed by different elements: emoticon. punctuation, interjections, and speech-to-text function of WeChat, and further studies the factors that assist speech-to-text emotion restoration. The research results reveal that emoticon and punctuation have a positive effect on the speech-to-text emotional restoration. The addition of the above two factors can restore the emotional effect of speech in text mode with lower loss, fully improve the user experience in mobile communication, and make the online communication smoother.
机译:近年来,随着人工智能技术的发展,语音识别技术可以对各种复杂环境下的语音进行高精度的解释和转录,提高打字效率。然而,通过语音翻译获得的文本仅由文本和简单的标点符号组成,这阻碍了用户真正的情感表达。苍白的译文阻碍了语境的形成,影响了语义的情感传递,导致用户与他人交流时的用户体验不佳。基于用户体验和情感,本文讨论了帮助语音到文本情感恢复的因素。通过定性和定量研究,本研究比较了由不同元素构成的信息文本的四种情感效应:表情符号。微信的标点符号、感叹词和语篇功能,并进一步研究有助于语篇情感恢复的因素。研究结果表明,表情符号和标点符号对语篇情感恢复有积极影响。上述两个因素的加入,可以以较低的损失恢复文本模式下语音的情感效果,充分改善移动通信中的用户体验,使在线通信更加顺畅。

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