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首页> 外文期刊>IEEE Transactions on Automatic Control >Voice extraction by on-line signal separation and recovery
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Voice extraction by on-line signal separation and recovery

机译：通过在线信号分离和恢复进行语音提取

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摘要

The paper presents a formulation and an implementation of a system for voice output extraction (VOX) in real-time and near-real-time realistic real-world applications. A key component includes voice-signal separation and recovery from a mixture in practical environments. The signal separation and extraction component includes several algorithmic modules with a variety of sophistication levels, which include dynamic processing neural networks in tandem with (dynamic) adaptive methods. These adaptive methods make use of optimization theory subject to the dynamic network constraints to enable practical algorithms. The underlying technology platforms used in the compiled VOX software can significantly facilitate the embedding of speech recognition intomany environments. Two demonstrations are described: one is PC-based and is near-real-time, the second is digital signal processing based and is real time. Sample results are described to quantify the performance of the overall systems.
机译：本文介绍了语音输出提取系统（VOX）在实时和近实时现实应用中的公式和实现。一个关键组件包括语音信号分离和在实际环境中从混合物中恢复。信号分离和提取组件包括多个具有各种复杂程度的算法模块，其中包括动态处理神经网络和（动态）自适应方法。这些自适应方法利用受动态网络约束约束的优化理论来实现实用算法。编译后的VOX软件中使用的底层技术平台可以显著促进语音识别嵌入到许多环境中。描述了两个演示：一个是基于PC的，几乎是实时的，第二个是基于数字信号处理的，是实时的。对示例结果进行了描述，以量化整个系统的性能。

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