Sparse representations for audio

音频的稀疏表示

• 批准号: 194542-2010
• 负责人: Lefebvre, Roch
• 金额: $ 2.4万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=509669
• 关键词: Sparse; representations; audio

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.

在过去的几十年里，数字音频处理的进步使许多应用程序出现，成熟，并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的核心都有一个共同的高级音频处理功能。具体来说，语音和/或音频压缩算法允许节省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程序的音频质量。对高性能音频处理算法，特别是压缩算法的需求，可以预期会随着诸如移动用户（例如在汽车中）的数字多通道无线电广播和在移动设备上使用的各种无线多媒体等要求苛刻的应用而增长。