Adaptive predictive coding of speech signals

By B. Atal, M. Schroeder. 1970

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In Speech & Audio

Citations in the corpus

Representation Learning with Contrastive Predictive Coding (2018, methodology): “This idea of predictive coding [5, 6] is one of the oldest techniques in signal processing for data compression.”
Audiodec: An Open-Source Streaming High-Fidelity Neural Audio Codec (2023, neutral): “Most of the conventional parametric codecs [6–8] were built according to in-domain knowledge of psychoacoustics, human speech production systems, and traditional digital signal processing.”
Cascaded Cross-Module Residual Learning towards Lightweight End-to-End Speech Coding (2019, background): “There have been various conventional speech coding methodologies, including linear predictive coding (LPC) [4], adaptive encoding [5], and perceptual weighting [6] among other domain specific knowledge about the speech signals, that are used to construct classic codecs, such as AMRWB [7] and OPUS [8”
Wavenet Based Low Rate Speech Coding (2017, background): “Ubiquitous are linear autoregressive (AR) models [7], and hidden Markov models (HMM) [8].”
Introduction to Digital Speech Processing (2007, background): “The essential features of predictive coding of speech were set forth in a classic paper by Atal and Schroeder [5], although the basic principles of predictive quantization were introduced by Cutler [26].”
Robust Low Rate Speech Coding Based on Cloned Networks and Wavenet (2020, methodology): “The emergence of digital signal processing led to the use of linear prediction to deﬁne features that describe the spectral envelope [4,5].”
Wasserstein Dependency Measure for Representation Learning (2019, background): “[45] which has connections to predictive coding in speech [4, 19], predictive processing in the brain [10, 41, 46] and the free energy principle [20].”