Lossless compression of audio data

数据压缩是使用比数据的常规表示所需的空间更少的空间来表示数据的过程。数据压缩可以是“无损”的，在这种情况下可以准确地恢复原始数据，也可以是“有损”的，即只能恢复原始数据的近似值。无损数据压缩适用于文本或其他类型的数据，在这些数据中，任何修改都会产生显著的有害影响。有损数据压缩通常用于图像或音频数据，其中降级程度是根据某种“可接受性”概念来调整的。由于围绕MP3文件共享的知识产权问题，音乐的有损压缩目前正进入公众的视线。虽然有损压缩适合于诸如随意欣赏音乐的应用，但在其他情况下是不合适的。例如，从被动声纳系统获得的音频数据通常具有非常低的信噪比(SNR)；即所需的声音被嵌入到相对嘈杂的环境噪声场中。通过使用有损压缩方案进一步降低SNR可能是不可接受的。此外，有损压缩技术通常基于心理声学原理，该原理规定人类将听不到某些声音(例如，宽松地说，在更响亮的声音之前或之后不久发生的安静的声音)；如果音频数据要由计算机软件处理，则这些原理是不合适的。本研究程序将研究音频数据的无损压缩，特别关注以下主题：(1)定义新的音频数据模型以优化可压缩性；(2)区分模型，如果有益，则针对声纳数据、音乐和语音；以及(3)检查特定压缩方案涉及的压缩工作量与解压缩工作量之间的权衡。

Data compression is the process of representing data using less space than that required by the data's normalrepresentation. Data compression can either be "lossless", in which case the original data can be recovered exactly, or "lossy", whereby only an approximation of the original data can be recovered. Lossless data compression is appropriate for textual or other kinds of data where any modifications would have significantdetrimental effects. Lossy data compression is frequently used for image or audio data, where the degree of degradation is adjusted according to some notion of "acceptability". Lossy compression of music is currently in the public eye because of intellectual property issues surrounding the sharing of MP3 files.While lossy compression is suitable for applications such as the casual enjoyment of music, in other situations it is not appropriate.  For example, audio data such as that obtained from passive sonar systems typically has a very low signal to noise ratio (SNR); that is, the desired sound is embedded in a relatively loud environmental noise field. Further degradation of the SNR by using a lossy compression scheme may be unacceptable. Also, lossy compression techniques are often based on psycho-acoustic principles which dictate that humans will not hear certain sounds (such as, loosely speaking, a quiet sound occurring shortly before or after a louder sound); these principles are inappropriate if the audio data is to be processed by computer software.This research program will study the lossless compression of audio data, with particular attention to the following topics: (1) defining new audio data models to optimize compressability; (2) differentiating thesemodels, if beneficial, towards sonar data, music and speech; and (3) examining the tradeoffs involved with compression effort vs. decompression effort for particular compression schemes.