In recent years, the proliferation of internet streaming
applications has brought about the need for low-bit rate speech and audio coding
methods. Several parametric designs such as the sinusoids+transients+noise model
have been somewhat successful for speech and audio synthesis. Low-bit rate and
streaming applications are restricted by only being able to transmit a limited
number of parameters for loudness estimation, resulting in reduced audio
quality. Current techniques for selecting relevant parameters are based on
either Signal to Mask Ratio (SMR) or loudness patterns. Despite their
popularity, an SMR focus has a tendency to neglect perceptually relevant
sinusoids, and the loudness focused methods are computationally costly and
aren?t proficient in delay?critical applications.
Researchers at Arizona State University have created a novel
and efficient technique for estimating relevant perceptual quantities like
loudness patterns of individual sinusoids. This routine is helpful for accurate
parameter selection in low-bit rate speech and audio applications.
Potential Applications
- Speech and Audio applications
- MPEG-4 HVXC speech coder
- MPEG-4 HILN audio coder
- MPEG-4 HVXC speech coder
- Low-Bit Rate applications
- Digital Audio Broadcasting
- Internet Streaming
- Digital Audio Broadcasting
- Volume Control
- Hearing Aid Technologies
Benefits and Advantages
- 90% faster CPU time for algorithm execution
- Sufficient computational efficiency for real-time use
- Less than 1/2 the loudness error of common method as
number of sinusoidal components selected increases