Spoken language is used by people to communicate naturally with one another. A simplistic
view of the communication process is as follows. Person A wishes to communicate an idea
to person B. The idea, initiated in the mind/brain of person A is encoded into speech
signals by means of the person A's speech production mechanism, the vocal apparata in
the vocal tract. Various kinds of noise may interfere with the speech signals as they travel
to person B. The resulting signal is captured by person B's speech receiving mechanism,
the ear. It is then analysed and decoded into a meaningful message by the brain of
person B.
This thesis concerns itself with the investigation of and attempt to automate the receiving
and decoding of English sentences using a machine - that is to perform the task of
person B in the above scenario using a computer. The aim is not only to produce a
sequence of phonetic sounds, but to look at the problems of building in the 'mind of the
machine', a picture of the meanings, intentions, absurdities and realities of the spoken
message.
The various models, algorithms and techniques of speech recognition and speech
understanding systems are examined. Speech signals are captured and digitised by
hardware. The digital samples are analysed and the important distinguishing features of all
speech sounds are identified. These are then used to classify speech sounds in subsequent
spoken words. The way speech sounds are joined together to form syllables and words
introduces difficult problems to the automatic recognition process. Speech sounds are
blurred, overlapped or left out due to the effects of coarticulation. Finally, natural language
processing issues, such as the importance of syntax (the structure) and semantics (the
meaning) of sentences, are studied.
A system to control and unite all the above processing is considered. The blackboard expert
system model of the widely reported HEARSAY-II speech recognition system is reviewed
as the system with the best potential for the above tasks. / Thesis (M.Sc.)-University of KwaZulu-Natal, 1992.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ukzn/oai:http://researchspace.ukzn.ac.za:10413/7881 |
| Date | January 1992 |
| Creators | Loureiro, Guy Marchand. |
| Contributors | Sartori-Angus, Alan G. |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
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