Improved voice control and transcription for wearable electronic devices

大多数人认为，智能手表等可穿戴电子设备糟糕的语音机界面让用户体验受挫。由于设备无法根据位置区分声音，导致语音识别容易受到风噪声和说话人重叠的影响，因此用户需要将设备移动到离自己嘴很近的地方。在许多情况下，此操作可以防止在语音控制期间查看屏幕。我们将研究利用萨里大学开发的盲源分离（BSS）技术改善语音控制和转录的可行性。我们工作的目标是将未经训练的单词识别错误率与单麦克风系统相比降低50%。这项工作具有很高的创新性，因为传统的源分离技术需要的胶囊分离太大（约15厘米），不适合智能手表的应用。这项技术的成功将使日常环境中的可穿戴设备能够轻松地口头输入命令和文本。

By most accounts the user experience with wearable electronic devices such as smartwatches is frustrated by the poor voice-machine interface. Due to the vulnerability of speech recognition to wind noise and overlapping talkers, caused by the devices' inability to discriminate sounds based on their location, the user is required to move the device very close to his/her mouth. In many situations this action prevents the screen from being viewed during voice control. We will investigate the feasibility of improving voice control and transcription using a blind source separation (BSS) technology developed at the University of Surrey. The objective of our work will be to reduce the untrained word recognition error rate by 50% compared to a single-mic system. This work is highly innovative because conventional source separation techniques require capsule separations that are too large (>15cm) for smartwatch applications. Success will transform the ease of inputting commands and text verbally into wearable devices in everyday settings.