检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]哈尔滨工业大学自动化测试与控制系,哈尔滨150001
出 处:《计算机研究与发展》1999年第9期1148-1152,共5页Journal of Computer Research and Development
基 金:.NULL.
摘 要: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,而且在单个声音模型识别率不高的情况下。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.
分 类 号:TN912.34[电子电信—通信与信息系统]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.177