一种基于数据融合的多话筒语音识别方法

识别率和对环境的适应能力是一个语音识别系统的两个重要性能，常见的提高语音识别率的方法大多通过改进声音模型来获得较高的识别率，这往往造成声音模型的复杂化以及模型训练的困难。另外，在说话人和麦克风位置不固定等情况下，这些方法识别效果往往很差。文中提出了一种用多话筒分别识别一个语音，并用数据融合技术对识别结果进行处理的语音识别方法。初步的实验结果表明该方法不仅可以提高系统对环境的适应能力，而且在单个声音

A METHOD OF MULTI-MICROPHONE SPEECH RECOGNITION BASED ON DATA FUSION

Recognition accuracy and adaptability is two of the most important capacity of a speech recognition system. A general method to improve speech recognition accuracy often focuses on improving acoustic model to obtain a higher recognition accuracy, which often leads to a complex model and difficult model training. In addition, in the case of unfixed position of speaker to microphone, its performance is often very bad. A new speech recognition method is brought forward,which uses multi|microphone to recognize Chinese syllables separately, and data fusion technique to process the recognition results. The preliminary experiment shows it not only can improve the system adaptability to environment, but also can reach a higher system recognition accuracy with a lower accuracy of each acoustic model.