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Introducing Song Form Intelligence Into Streaming Audio

机译:将歌曲形式智能介绍为流媒体音频

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When receiving streaming media over a low bandwidth wireless connection, users can experience not only packet losses but also extended service interruptions. During this time no packets are received and, if not addressed, these dropped packets cause unacceptable interruptions in the audio stream. A long dropout of this kind may be overcome by ensuring that the buffer at the client is large enough. However, when using fixed bit rate technologies this may only be done by buffering packets for an extended period before starting to play the track. During this period, many users are likely to lose interest or become frustrated. This paper presents a novel semantic audio error concealment algorithm which enables the audio to start playing within two or three seconds, while at the same time using a small proportion of the available bandwidth to fill the client device buffer with received packets but categorised into structures of the song. A pattern matching run-time algorithm works to identify portions of the audio stream and when a dropout does occur - the relevant sections of the buffered audio are inserted so as to create a perfect match for the lost audio. Our algorithm can be shown to increase reliability on bursty wireless networks.
机译:在通过低带宽无线连接上接收流媒体时,用户不仅可以体验数据包丢失,还可以延长服务中断。在此期间,没有收到数据包,如果没有解决,则这些丢弃的数据包在音频流中导致不可接受的中断。可以通过确保客户处的缓冲器足够大,克服这种长大辍学。但是,当使用固定比特率技术时,这只能通过在开始播放轨道之前长时间缓冲分组来完成。在此期间,许多用户可能会失去兴趣或沮丧。本文提出了一种新颖的语义音频错误隐藏算法,使音频能够在两到三秒内开始播放,而使用小比例的可用带宽来填充具有接收的数据包的客户端设备缓冲区,而是分为结构这首歌。模式匹配运行时算法适用于识别音频流的部分,并且当发生丢失时 - 将插入缓冲音频的相关部分以便为丢失的音频创建完美匹配。我们的算法可以显示在突发无线网络上提高可靠性。

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