Clean Audio for TV broadcast: An Object-Based Approach for Hearing-Impaired Viewers - April 2015
Audibility of a CD-Standard A/DA/A Loop Inserted into High-Resolution Audio Playback - September 2007
Sound Board: Food for Thought, Aesthetics in Orchestra Recording - April 2015
An Improved Low Complexity AMR-WB+ Encoder Using Neural Networks for Mode Selection
This paper presents an alternative mode selector based on neural networks to improve the low-complexity AMR WB+ standard audio coder especially at low bit rates. The AMR-WB+ audio coder is a multi-mode coder using both time-domain and frequency-domain modes. In low complexity operation, the standard encoder determines the coding mode on a frame-by-frame basis by essentially applying thresholding to parameters extracted from the input signal and using a logic which favors time-domain modes. The mode selector proposed in this paper reduces this bias, and achieves a mode decision which is closer to the full complexity encoder. This results in measurable quality improvements, in both objective and subjective assessments.
Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $20 for non-members, $5 for AES members and is free for E-Library subscribers.