Electrical audio signal processing systems and devices – Hearing aids – electrical – Specified casing or housing
Patent
1990-09-26
1993-06-22
Knepper, David D.
Electrical audio signal processing systems and devices
Hearing aids, electrical
Specified casing or housing
381 30, 381 31, G01L 900
Patent
active
052221890
DESCRIPTION:
BRIEF SUMMARY
TECHNICAL FIELD
The invention relates in general to the high-quality low bit-rate digital signal processing of audio signals, such as music signals. More particularly, the invention relates to transform encoders and decoders for such signals, wherein the encoders and decoders have a short signal-propagation delay. Short delays are important in applications such as broadcast audio where a speaker must monitor his own voice. A delay in voice feedback causes serious speech disruption unless the delay is very short.
BACKGROUND ART
INTRODUCTION
Transform coding of high-quality signals in the prior art have used long signal sample block lengths to achieve low bit-rate coding without creating objectionable audible distortion. For example, a transform coder disclosed in EP 0 251 028 uses a block length of 1024 samples. Long block lengths have been necessary because shorter blocks degrade transform coder selectivity. Filter selectivity is critical because transform coders with sufficient filter bank selectivity can exploit psychoacoustic masking properties of human hearing to reduce bit-rate requirements without degrading the subjective quality of the coded signal.
Coders using long block lengths suffer from two problems: (1) audible distortion of signals with large transients caused by the temporal spreading of the transient's effects throughout the transform block, and (2) excessive propagation delay of the signal through the encoding and decoding process. In prior art coders, these processing delays are too great for applications such as broadcast audio where a speaker must monitor his own voice. A delay in voice feedback causes serious speech disruption unless the delay is kept very short.
The background art is discussed in more detail in the following Background Summary.
BACKGROUND SUMMARY
There is considerable interest among those in the field of signal processing to discover methods which minimize the amount of information required to represent adequately a given signal. By reducing required information, signals may be transmitted over communication channels with lower bandwidth, or stored in less space. With respect to digital techniques, minimal informational requirements are synonymous with minimal binary bit requirements.
Two factors limit the reduction of bit requirements:
(1) A signal of bandwidth W may be accurately represented by a series of samples taken at a frequency no less than 2.multidot.W. This is the Nyquist sampling rate. Therefore, a signal T seconds in length with a bandwidth W requires at least 2.multidot.W.multidot.T number of samples for accurate representation.
(2) Quantization of signal samples which may assume any of a continuous range of values introduces inaccuracies in the representation of the signal which are proportional to the quantizing step size or resolution. These inaccuracies are called quantization errors. These errors are inversely proportional to the number of bits available to represent the signal sample quantization.
If coding techniques are applied to the full bandwidth, all quantizing errors, which manifest themselves as noise, are spread uniformly across the bandwidth. Techniques which may be applied to selected portions of the spectrum can limit the spectral spread of quantizing noise. Two such techniques are subband coding and transform coding. By using these techniques, quantizing errors can be reduced in particular frequency bands where quantizing noise is especially objectionable by quantizing that band with a smaller step size.
Subband coding may be implemented by a bank of digital bandpass filters. Transform coding may be implemented by any of several time-domain to frequency-domain transforms which simulate a bank of digital bandpass filters. Although transforms are easier to implement and require less computational power and hardware than digital filters, they have less design flexibility in the sense that each bandpass filter "frequency bin" represented by a transform coefficient has a uniform bandwidth. By contrast, a bank of digital bandpass
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Dolby Laboratories Licensing Corporation
Gallagher Thomas A.
Knepper David D.
Lathrop David N.
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