Introduction to Digital Audio Coding and Standards
By M. Bosi, Richard E. Goldberg, Joan L. Mitchell. 2004
369 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Ming-Hsuan Yang
- Dacheng Tao
- Vladlen Koltun
- Trevor Darrell
- Jitendra Malik
- Bernt Schiele
- Andrew Zisserman
In Signal Processing
- Nicholas Carlini
- Ian J. Goodfellow
- Qifeng Chen
- Vladlen Koltun
- Tinku Acharya
- François G. Germain
- Yao Qin
- Hong-Goo Kang
Citations in the corpus
- Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis (2023, methodology): “In practice, the STFT is computed by taking a sequence of Fast Fourier Transforms (FFTs) on overlapping, windowed frames of data, which are created as the window function advances or “hops” through time.”
- Speech Denoising with Deep Feature Losses (2018, background): “Challenges also arise in mediated human-to-human communication, as perception mechanisms can make small errors still noticeable by the average user [2].”
- End-to-End Neural Audio Coding in the MDCT Domain (2023, methodology): “Our approach retains the MDCT-based analysis/synthesis framework from the legacy codecs but restructures the encoding process of MDCT bins and the bit-allocation mechanism [1] using neural architectures to allow for gradient backpropagation [20] throughout the system.”
- Introduction to Data Compression (2005, methodology): “Goldberg [194] provides a detailed accounting of the standards described here as well as a comprehensive look at the process of constructing a psychoacoustic model.”
- Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching (2016, background): “In this section, we present a small overview of some important psychoacoustic principles; a more thorough treatment can be found in (Cook, 1999; Bosi and Goldberg, 2012).”
- Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition (2019, methodology): “For further background on psychoacoustic models, we refer the interested reader to (Lin & Abdulla, 2015; Mitchell, 2004).”