Sparse representations for audio

在过去的几十年里，数字音频处理的进步使许多应用程序得以出现和成熟，在许多情况下成为日常生活中的商品。手机、智能手机、MP3播放器、IP语音(VoIP)软件，甚至YouTube，其核心都有共同的高级音频处理。具体地说，语音和/或音频压缩算法允许节约地使用传输带宽和存储空间，同时为用户提供他们期望的给定应用的音频质量。可以预期，随着移动用户的数字多声道无线电广播(例如，在汽车中)和移动设备上使用的各种无线多媒体等要求苛刻的应用，对高性能音频处理算法，特别是压缩算法的需求将会增长。

Over the past decades, advances in digital audio processing have allowed numerous applications to emerge, mature and in many cases become commodities in everyday life. Cellphones, smartphones, MP3 players, Voice over IP (VoIP) software and even Youtube all have in common advanced audio processing in their core. Specifically, speech and/or audio compression algorithms allow using transmission bandwidth and storage space sparingly while providing users the audio quality they expect for a given application. The need for performant audio processing algorithms, and in particular compression algorithms, can be expected to grow with demanding applications such as digital multichannel radio broadcast for mobile users (in cars, for example) and wireless multimedia of all sorts to be used on mobile devices.