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Speech Coding : Code- Excited Linear Prediction / by Tom Bäckström

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Signals and Communication Technology | SpringerLink Bücher | Springer eBook Collection EngineeringPublisher: Cham : Springer, 2017Description: Online-Ressource (XXI, 240 p. 76 illus, online resource)ISBN:
  • 9783319502045
Subject(s): Additional physical formats: 9783319502021 | Druckausg.: 978-3-319-50202-1 | Erscheint auch als: Speech coding. Druck-Ausgabe Cham : Springer, 2017. xxi, 240 SeitenDDC classification:
  • 621.382
RVK: RVK: ZN 6060LOC classification:
  • TK5102.9 TA1637-1638 TK7882.S65
  • TK5102.9
  • TA1637-1638
  • TK7882.S65
DOI: DOI: 10.1007/978-3-319-50204-5Online resources: Summary: This book provides scientific understanding of the most central techniques used in speech coding both for advanced students as well as professionals with a background in speech audio and or digital signal processing. It provides a clear connection between the whys hows and whats thus enabling a clear view of the necessity purpose and solutions provided by various tools as well as their strengths and weaknesses in each respect Equivalently this book sheds light on the following perspectives for each technology presented Objective What do we want to achieve and especially why is this goal important Resource Information What information is available and how can it be useful and Resource Platform What kind of platforms are we working with and what are their capabilities restrictions This includes computational memory and acoustic properties and the transmission capacity of devices used. The book goes on to address Solutions Which solutions have been proposed and how can they be used to reach the stated goals and Strengths and weaknesses In which ways do the solutions fulfill the objectives and where are they insufficient Are resources used efficiently. This book concentrates solely on code excited linear prediction and its derivatives since mainstream speech codecs are based on linear prediction It also concentrates exclusively on time domain techniques because frequency domain tools are to a large extent common with audio codecsSummary: Introduction -- Usage -- Known Problems -- ImplementationPPN: PPN: 1657560465Package identifier: Produktsigel: ZDB-2-ENG
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