Visual Solutions for Automated Translation Between Spoken and Signed Languages

口语和手语之间自动翻译的可视化解决方案。我们建议建立一个强大的视觉语音识别系统，分析图像的口语，并实现了识别的话语与至少人类专家的识别率。然后，这个视觉语音识别系统将与我们现有的手势识别系统集成，以提高性能，就像人类联合收割机视觉和音频数据进行语言理解一样。其结果将是一个系统，在实际应用领域提供英语和澳大利亚手语Auslan之间的翻译。值得注意的是，我们的工作将为连接语言和手势的神经活动的认知模型提供见解。

Visual Solutions for Automated Translation Between Spoken and Signed Languages. We propose to build a robust visual speech recognition system that analyzes images of spoken language and achieves a recognition of the utterances with at least human expert recognition rates. This visual speech recognition system will then be integrated with our existing gesture recognition system to improve performance, just as humans combine visual and audio data for language understanding. The result will be a system providing translation between English and the Australian sign language Auslan in a practical application domain. Significantly, our work will provide insights into the cognitive models of neural activity linking language and gesture.