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An Automatic Real Time Speech-Speaker Recognition System: A Real Time Approach

机译：自动实时语音扬声器识别系统：实时方法

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In this paper, an automatic speech-speaker recognition system is implemented in real time noisy environment. The database creation with personalized voice in noisy environment is done with microphone arrangement. Various techniques in preprocessing step can be used to remove noise from sampled voice signal. Mel Frequency Cepstral Coefficient (MFCC) technique is used to extract Mel Cepstral Coefficients from each speech sample and thus database is created during training phase. For testing purpose, each input sampled speech signal is mapped with stored database using Vector Quantization (VQ) and Dynamic Time Warping (DTW) techniques. Output of mapped VQ is Speaker Recognition and output of mapped DTW is Speech Recognition. Using single sampled voice, real time Speech and Speaker can be recognized. This system is very useful for various applications such as Forensic, Banking where security is at highest priority.
机译：本文在实时嘈杂的环境中实现了一种自动语音扬声器识别系统。在嘈杂环境中具有个性化语音的数据库创建是以麦克风排列完成的。预处理步骤中的各种技术可用于从采样语音信号中去除噪声。 MEL频率谱系距（MFCC）技术用于从每个语音样本中提取MEL谱系齐数，因此在训练阶段期间创建数据库。对于测试目的，每个输入采样的语音信号使用矢量量化（VQ）和动态时间翘曲（DTW）技术映射使用存储的数据库。映射VQ的输出是扬声器识别和映射DTW的输出是语音识别。使用单一采样的声音，可以识别实时语音和扬声器。该系统对各种应用非常有用，例如法医，银行业务，其中安全性处于最优先级。

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