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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Recovering sound sources from embedded repetition
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Recovering sound sources from embedded repetition

机译：从嵌入的重复中恢复声源

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摘要

Cocktail parties and other natural auditory environments present organisms with mixtures of sounds. Segregating individual sound sources is thought to require prior knowledge of source properties, yet these presumably cannot be learned unless the sources are segregated first. Here we show that the auditory system can bootstrap its way around this problem by identifying sound sources as repeating patterns embedded in the acoustic input. Due to the presence of competing sounds, source repetition is not explicit in the input to the ear, but it produces temporal regularities that listeners detect and use for segregation. We used a simple generative model to synthesize novel sounds with naturalistic properties. We found that such sounds could be segregated and identified if they occurred more than once across different mixtures, even when the same sounds were impossible to segregate in single mixtures. Sensitivity to the repetition of sound sources can permit their recovery in the absence of other segregation cues or prior knowledge of sounds, and could help solve the cocktail party problem.
机译：鸡尾酒会和其他自然听觉环境使生物体混合在一起。隔离单个声源被认为需要先了解声源的属性，但是除非先将声源进行隔离，否则大概无法学习这些知识。在这里，我们表明听觉系统可以通过将声源识别为嵌入在声音输入中的重复模式来解决此问题。由于存在竞争声音，因此源重复在耳朵的输入中并不明确，但会产生时间规律性，供听众检测并用于隔离。我们使用简单的生成模型来合成具有自然属性的新颖声音。我们发现，即使在相同的声音不可能在单个混合物中分离的情况下，如果这些声音在不同的混合物中出现不止一次，也可以将其分离和识别。对声源重复的敏感度可以在没有其他隔离提示或声音先验知识的情况下恢复它们，并有助于解决鸡尾酒会的问题。

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