Detecting language structure in audio signals

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Having received a signal, unlike traditional speech processing, the aim of this research goal is not to identify where individual word boundaries begin and end or detect the pattern set, using supervised techniques, which comprise the signal s lexicon. The rationale that underpins this approach is therefore, not to decipher the audio signal content as this is a secondary task and assumes language content exists, but to identify what constitutes the physical structure of spoken language, in contrast to other structured phenomena. In essence, to develop an automated (artificially intelligent) intuitive ear that can detect the rhythm and structure of language with the same accuracy (or better) of the human ear. To achieve this, unsupervised learning techniques, which do not rely on prior knowledge of a specific system, underpin generic methods devised, to facilitate classification of unknown phenomena, if encountered.
Original languageEnglish
Title of host publicationProceedings of the International conference on Computer, Communication and Control Technologies (CCCT ’04)
EditorsHsing-Wei Chu
Place of PublicationAustin, TX
PublisherInternational Institute of Informatics and Systemics (IIIS)
Number of pages6
Publication statusPublished - 14 Aug 2004
EventInternational Conference on Computing, Communications and Control Technologies (CCCT'04) - University of Texas, Austin, TX, United States
Duration: 14 Aug 200417 Aug 2004


ConferenceInternational Conference on Computing, Communications and Control Technologies (CCCT'04)
Country/TerritoryUnited States
CityAustin, TX
Internet address


  • Audio
  • Language
  • Unsupervised learning
  • Significant Activity Segments (SAS)
  • Detection


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