"Scalable Audio Compression for Multimedia Applications"

可扩展的信号压缩算法是由不断发展的通信网络，这是由各种各样的信道具有广泛不同的静态和动态容量，并通过最近的趋势，向增量容量和带宽预留信道所需要的。目前的多媒体压缩算法隐含地假设简单的点对点传输以及固定的带宽分配，并导致网络资源的利用率不足。真正可扩展的编码器的发展与速率控制的本地源统计，网络流量负载，和信道条件将直接影响下一代的音频互联网的多播，可视电话，视频会议，和各种应用程序的信息检索从多媒体数据库。本研究的重点是新的音频压缩技术的语音和音乐信号，允许有效的缩放的比特率和音频带宽的框架内的多媒体压缩。主要的推力集中在音频信号建模与正弦信号表示，这是带宽和速率可伸缩的，并实现了良好的性能，在各种编码环境中，从低速率编码的窄带语音（2 kb/s）的高质量编码的音频信号（16-64 kb/s）。正在研究的方法包括复杂的语音和音乐分类，以允许内容自适应音频分解和建模，广义乘积码矢量量化，特别是多级矢量量化，以实现可伸缩量化技术。研究了音视频信号联合压缩的流间优化技术，重点研究了其在数据包传输，特别是TCP/IP互联网协议中的应用。一个重要的子问题是流间速率分配优化，考虑到每个流的活动水平，用户需求，以及对量化和信道误差的敏感性。信源e信道编码和错误隐藏问题进行了研究，以保持有线和无线信道的数据包丢失下的服务质量要求。

Scalable signal compression algorithms are required by the evolving communication network, which is composed of a variety of channels with widely differing static and dynamic capacities, and by the recent trend toward incremental capacity and bandwidth reservation channels. Current multimedia compression algorithms implicitly assume simple point to point transmission as well as fixed bandwidth allocation, and result in under-utilization of the network resources. The development of truly scalable coders with rate controlled by the local source statistics, network traffic load, and channel condition will directly impact the next generation of audio internetworking for multicasting, videotelephone, videoteleconferencing, and various applications for information retrieval from multimedia databases. This research focuses on new audio compression techniques for voice and music signals, that allow efficient scaling of bit rate and audio bandwidth within the framework of multimedia compression. The primary thrust centers on audio signal modeling with a sinusoidal signal representation, which is bandwidth and rate scalable and achieves good performance in a variety of coding environments from low-rate coding of narrow-band speech (2 kb/s) to high-quality coding of audio signals (16-64 kb/s). Methods under investigation include sophisticated phonetic and music classification to allow content-adaptive audio decomposition and modeling, generalized product code vector quantization, and in particular, multi- stage vector quantization, to implement scalable quantization techniques. Inter- stream optimization for joint compression of audio and video signals is studied with emphasis on potential applicability to packet transmission and in particular to TCP/IP Internet protocols. An important sub-problem is the inter-stream rate allocation optimization taking into account each stream's level of activity, user requirements, and sensitivity to quantization and channel errors. Sourc e-channel coding and error concealment issues are studied in order to maintain quality of service requirements under packet losses for both wired and wireless channels.