Intelligent equipment is a kind of device that is characterized by intelligent sensor interconnections, big data processing, new types of displays, human-machine interaction and so on for the new generation of informa...Intelligent equipment is a kind of device that is characterized by intelligent sensor interconnections, big data processing, new types of displays, human-machine interaction and so on for the new generation of information technology. For this purpose, in this paper, first, we present a type of novel intelligent deep hybrid neural network algorithm based on a deep bidirectional recurrent neural network integrated with a deep backward propagation neural network. It has realized acoustic analysis, speech recognition and natural language understanding for jointly constituting human-machine voice interactions. Second, we design a voice control motherboard using an embedded chip from the ARM series as the core, and the onboard components include ZigBee, RFID, WIFI, GPRS, a RS232 serial port, USB interfaces and so on. Third, we take advantage of algorithms, software and hardware to make machines “understand” human speech and “think” and “comprehend” human intentions to structure critical components for intelligent vehicles, intelligent offices, intelligent service robots, intelligent industries and so on, which furthers the structure of the intelligent ecology of the Internet of Things. At last, the experimental results denote that the study of the semantics interaction controls based on an embedding has a very good effect, fast speed and high accuracy, consequently realizing the intelligent ecology construction of the Internet of Things.展开更多
啸叫干扰是语音通信系统中普遍存在的问题,常由扬声器与传声器之间的声反馈引发,严重影响语音质量与系统稳定性。针对传统方法在频率漂移、多频啸叫及实时性能方面的局限,提出一种融合多维特征检测与动态Notch滤波控制的啸叫抑制方法。...啸叫干扰是语音通信系统中普遍存在的问题,常由扬声器与传声器之间的声反馈引发,严重影响语音质量与系统稳定性。针对传统方法在频率漂移、多频啸叫及实时性能方面的局限,提出一种融合多维特征检测与动态Notch滤波控制的啸叫抑制方法。该方法利用均方根(Root Mean Square,RMS)能量趋势、频谱峰值结构、谐波分布及频率稳定性等多特征构建复合检测模型,能够有效区分啸叫、人声与短时冲击信号。在频率定位方面,设计频谱插值细化算法,提高了中心频率估计精度。在滤波控制方面,引入动态响应与自动释放机制,实现Notch滤波器的自适应调节。实验结果表明,该方法在多种典型啸叫场景下均表现出良好的抑制性能与语音保真度,具有较强的实时性与工程可用性。展开更多
文摘Intelligent equipment is a kind of device that is characterized by intelligent sensor interconnections, big data processing, new types of displays, human-machine interaction and so on for the new generation of information technology. For this purpose, in this paper, first, we present a type of novel intelligent deep hybrid neural network algorithm based on a deep bidirectional recurrent neural network integrated with a deep backward propagation neural network. It has realized acoustic analysis, speech recognition and natural language understanding for jointly constituting human-machine voice interactions. Second, we design a voice control motherboard using an embedded chip from the ARM series as the core, and the onboard components include ZigBee, RFID, WIFI, GPRS, a RS232 serial port, USB interfaces and so on. Third, we take advantage of algorithms, software and hardware to make machines “understand” human speech and “think” and “comprehend” human intentions to structure critical components for intelligent vehicles, intelligent offices, intelligent service robots, intelligent industries and so on, which furthers the structure of the intelligent ecology of the Internet of Things. At last, the experimental results denote that the study of the semantics interaction controls based on an embedding has a very good effect, fast speed and high accuracy, consequently realizing the intelligent ecology construction of the Internet of Things.
文摘啸叫干扰是语音通信系统中普遍存在的问题,常由扬声器与传声器之间的声反馈引发,严重影响语音质量与系统稳定性。针对传统方法在频率漂移、多频啸叫及实时性能方面的局限,提出一种融合多维特征检测与动态Notch滤波控制的啸叫抑制方法。该方法利用均方根(Root Mean Square,RMS)能量趋势、频谱峰值结构、谐波分布及频率稳定性等多特征构建复合检测模型,能够有效区分啸叫、人声与短时冲击信号。在频率定位方面,设计频谱插值细化算法,提高了中心频率估计精度。在滤波控制方面,引入动态响应与自动释放机制,实现Notch滤波器的自适应调节。实验结果表明,该方法在多种典型啸叫场景下均表现出良好的抑制性能与语音保真度,具有较强的实时性与工程可用性。
