DeepVoCoder: A CNN Model for Compression and Coding of Narrow Band Speech
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10242237" target="_blank" >RIV/61989100:27240/19:10242237 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/19:10242237
Result on the web
<a href="https://ieeexplore.ieee.org/document/8730308" target="_blank" >https://ieeexplore.ieee.org/document/8730308</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2019.2920663" target="_blank" >10.1109/ACCESS.2019.2920663</a>
Alternative languages
Result language
angličtina
Original language name
DeepVoCoder: A CNN Model for Compression and Coding of Narrow Band Speech
Original language description
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 IP telephony and telecommunications purposes. The model takes time domain speech samples as inputs and encodes them using a cascade of convolutional filters in multiple layers, where pooling is applied after some layers to downsample the encoded speech by half. The final bottleneck layer of the CNN encoder provides an abstract and compact representation of the speech signal. In this paper, it is demonstrated that this compact representation is sufficient to reconstruct the original speech signal in high quality using the CNN decoder. This paper also discusses the theoretical background of why and how CNN may be used for end-to-end speech compression and coding.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20203 - Telecommunications
Result continuities
Project
<a href="/en/project/LM2015070" target="_blank" >LM2015070: IT4Innovations National Supercomputing Center</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Access
ISSN
2169-3536
e-ISSN
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Volume of the periodical
7
Issue of the periodical within the volume
Neuveden
Country of publishing house
US - UNITED STATES
Number of pages
9
Pages from-to
75081-75089
UT code for WoS article
000473188800001
EID of the result in the Scopus database
2-s2.0-85068349969