AES Los Angeles 2016
Paper Session P25
P25 - Signal Processing—Part 5
Sunday, October 2, 10:45 am — 12:15 pm (Rm 409B)
Chair:
Scott Norcross, Dolby Laboratories - San Francisco, CA, USA
P25-1 An Efficient Algorithm for Clipping Detection and Declipping Audio—Christopher Laguna, Georgia Institute of Technology - Atlanta, GA, USA; Alexander Lerch, Georgia Institute of Technology - Atlanta, GA, USA
We present an algorithm for end to end declipping, which includes clipping detection and the replacement of clipped samples. To detect regions of clipping, we analyze the signal’s amplitude histogram and the shape of the signal in the time-domain. The sample replacement algorithm uses a two-pass approach: short regions of clipping are replaced in the time-domain and long regions of clipping are replaced in the frequency-domain. The algorithm is robust against different types of clipping and is efficient compared to existing approaches. The algorithm has been implemented in an open source JavaScript client-side web application. Clipping detection is shown to give an f-measure of 0.92 and is robust to the clipping level.
Convention Paper 9682 (Purchase now)
P25-2 A Two-Pass Algorithm for Automatic Loudness Correction—Alexey Lukin, iZotope, Inc. - Cambridge, MA, USA; Russell McClellan, iZotope, Inc. - Cambridge, MA, USA; Aaron Wishnick, iZotope - Cambridge, MA, USA
Loudness standards for broadcast audio, such as BS.1770, establish target values for the integrated loudness, true peak level, and short-term loudness of a record. Compliance with these three targets can be challenging when the dynamic range of a record is high, so software for automatic loudness correction is important for speeding up the workflow of post-production engineers. This work reviews existing software implementations of automatic loudness correction and proposes a new algorithm that provides efficient simultaneous correction of all three targets.
Convention Paper 9683 (Purchase now)
P25-3 A Low Computational Complexity Beamforming Scheme Concatenated with Noise Cancellation—Jin Xie, Marvell Technology Group Ltd. - Santa Clara, CA, USA; Sungyub Daniel Yoo, Marvell Technology Group Ltd. - Santa Clara, CA, USA; Kapil Jain, Marvell Technology Group Ltd. - Santa Clara, CA, USA
In this paper we present a microphone beamforming algorithm. This algorithm has been implemented in Marvell’s proprietary digital signal processor embedded in Marvell’s audio codec chip. This beamforming algorithm features (1) easy to implement; (2) sound source localization (SSL) and sound source tracking, (3) single in single out frequency domain noise cancellation. Lab tests show that the performance is better than the reference existing codec.
Convention Paper 9684 (Purchase now)