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Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2016 Most current very low bit rate (VLBR) speech coding systems use hidden Markov model (HMM) based speech recognition and synthesis techniques. This allows transmission of information (such as phonemes) segment by segment; this decreases the bit rate ...
M. Cernak +3 more
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8～64kbit/s super-wideband embedded speech and audio coding algorithm
Tongxin xuebao, 2009 Based on the international telecommunication union telecommunication standardization sector （ITU-T） recommendation G.729.1 and modified modulated lapped transform （MLT） coding, a super-wideband embedded variable bit-rate speech and audio coding algorithm
JIA Mao-shen, BAO Chang-chun, LI Rui
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APVQ encoder applied to wideband speech coding [PDF]
, 1996 The paper describes a coding scheme for broadband speech (sampling frequency 16 KHz). The authors present a wideband speech encoder called APVQ (adaptive predictive vector quantization).
Masgrau Gómez, Enrique José +1 more
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Nature Communications, 2020 On-line comprehension of natural speech requires segmenting the acoustic stream into discrete linguistic elements. This process is argued to rely on theta-gamma oscillation coupling, which can parse syllables and encode them in decipherable neural ...
Sevada Hovsepyan +2 more
semanticscholar +1 more source
A Noise Reduction Preprocessor for Mobile Voice Communication
EURASIP Journal on Advances in Signal Processing, 2004 We describe a speech enhancement algorithm which leads to significant quality and intelligibility improvements when used as a preprocessor to a low bit rate speech coder.
Rainer Martin +3 more
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Vector-Quantized Autoregressive Predictive Coding [PDF]
Interspeech, 2020 Autoregressive Predictive Coding (APC), as a self-supervised objective, has enjoyed success in learning representations from large amounts of unlabeled data, and the learned representations are rich for many downstream tasks.
Yu-An Chung, Hao Tang, James R. Glass
semanticscholar +1 more source
DeepVoCoder: A CNN model for compression and coding of narrow band speech [PDF]
, 2019 This paper proposes a convolutional neural network (CNN)-based encoder model to compress and code speech signal directly from raw input speech. Although the model can synthesize wideband speech by implicit bandwidth extension, narrowband is preferred for
Ilk, Hakki Gokhan +3 more
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Dissecting neural computations of the human auditory pathway using deep neural networks for speech
bioRxiv, 2022 The human auditory system extracts rich linguistic abstractions from the speech signal. Traditional approaches to understand this complex process have used classical linear feature encoding models, with limited success.
Yuanning Li +5 more
semanticscholar +1 more source
Improved embedded wideband speech codec fitting EV-VBR standard
Tongxin xuebao, 2010 Based on the International Telecommunication Union Telecommunication Standardization Sector（ITU-T） recommendation for EV-VBR coding standard and the candidate codec designed by Speech and Audio Signal Processing Laboratory（SASPL） of Beijing University of
XIN Jie +3 more
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Mixture Density Networks, Human Articulatory Data and Acoustic-to-Articulatory Inversion of Continuous Speech [PDF]
, 2001 Researchers have been investigating methods for retrieving the articulation underlying an acoustic speech signal for more than three decades. A successful method would find many applications, for example: low bit-rate speech coding, helping individuals ...
Richmond, K.
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