rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Phonetic Search Methods for Large Speech Databases
  name:
    name part: Moyal, Ami.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Aharonson, Vered.
    role:
      role term: author.
  name:
    name part: Tetariy, Ella.
    role:
      role term: author.
  name:
    name part: Gishri, Michal.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2013
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: X, 53 p. 21 illus., 6 illus. in color. online resource.
  abstract: “Phonetic Search Methods for Large Databases” focuses on Keyword Spotting (KWS) within large speech databases. The brief will begin by outlining the challenges associated with Keyword Spotting within large speech databases using dynamic keyword vocabularies. It will then continue by highlighting the various market segments in need of KWS solutions, as well as, the specific requirements of each market segment. The work also includes a detailed description of the complexity of the task and the different methods that are used, including the advantages and disadvantages of each method and an in-depth comparison. The main focus will be on the Phonetic Search method and its efficient implementation. This will include a literature review of the various methods used for the efficient implementation of Phonetic Search Keyword Spotting, with an emphasis on the authors’ own research which entails a comparative analysis of the Phonetic Search method which includes algorithmic details. This brief is useful for researchers and developers in academia and industry from the fields of speech processing and speech recognition, specifically Keyword Spotting.
  table of contents: Keyword Spotting out of Continuous Speech -- Introduction -- Problem Formulation: KWS in Large Speech Databases -- Target Applications of Keyword Spotting -- Keyword Spotting Methods -- LVCSR-Based KWS -- Acoustic KWS -- Phonetic Search KWS -- Discussion: Why Phonetic Search? -- Response Time -- KWS Performance -- Keyword Flexibility -- Phonetic Search -- The Search Mechanism -- Using Phonetic Search for KWS -- Computational Complexity Analysis -- Search Space Complexity Reduction -- Overview -- Complexity Reduction in Phonetic Search -- Anchor-based Phonetic Search -- Evaluating Phonetic Search KWS -- Performance Metrics -- Evaluation Process -- Evaluation Databases -- Evaluation Results -- Exhaustive Search. - Textual Benchmark -- KWS on Speech -- Anchor-based Search -- Textual Benchmark -- Reduced Complexity KWS on Speech -- Multiple Thresholds -- Lessons Learned from the Evaluation -- Summary -- Glossary of Acronyms -- References.
  note: by Ami Moyal, Vered Aharonson, Ella Tetariy, Michal Gishri.
  subject:
    topic: Engineering
  subject:
    topic: Computational linguistics
  subject:
    topic: Engineering
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Language Translation and Linguistics
  subject:
    topic: Computational Linguistics
  classification: TK5102.9
  classification: TA1637-1638
  classification: TK7882.S65
  classification: 621.382
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: SpringerBriefs in Electrical and Computer Engineering
  identifier: 9781461464891
  identifier: http://dx.doi.org/10.1007/978-1-4614-6489-1
  record info:
    record creation date: 130228
    record change date: 20151028141727.0
    record identifier: 978-1-4614-6489-1