可穿戴计算音频信息压缩的上下文相关通知模型

Notification model of wearable computing context-sensitive audio information compression

针对传统的可穿戴计算音频信息压缩采用插入的通知方法所产生的通知线索缺乏差异性问题,设计了基于上下文相关的动态适应通知模型:根据外围设备的周围暗示、动态压缩、使用频率、通知级别等级、使用水平和环境变量来动态地选择合适的通知策略,从而使用户能用语音识别和语音合成对通知信息进行差异性处理.实例验证了此模型的有效性,该模型可在优化音频技术和通知模型的系统中推广使用.

Wearable computing for traditional audio information compression method by inserting a notice leads generated by the lack of difference between the notification problem,we designed a dynamic adaptation based on context-sensitive notification model.The model is based around peripherals implied,dynamic compression,frequency of use,notice-level grade,level and environmental variables used to dynamically select the appropriate notification strategy,so that users can use speech recognition and speech synthesis on the notification information processing differences.Example shows the validity of this model,the model can be notified in the optimization model for audio technology and systems being widely used.