word boundary- hypothesisation in hindi speech - Speech and ...

frame. This technique also achieved more than 90% recognition accuracy on a
connected digit recognition task involving sequences of four ~a~anesk digits.
Both the abovz techniques achieved a recognition accuracy of 90% or more and
recognised many word boundaries. However both the techniques were task and
vocabulary dependent and were tested only on small vocabularies (100 words or less).
Extending them to task independent and large vocabulary continuous speech
recognition will require large training and hence they are not suitable in the context of
continuous speech recognition.
Whiie the above techniques were not applicable for word boundary
hypothesisation in continuous speech, they have shown that spectral clues do exist for
hypothesising word boundaries. In our studies, reported in chapter 6, some spectral
features based on the acoustic-phonetic knowledge were used as clues for word
boundary hypothesisation in continuous speech.
2.3.5 Word boundary hypothesisation techniques for Hindi
All of the earlier studies reviewed above were performed for English and in a
few cases for German and Japanese languages. In the context of word boundary
hypothesisation for continuous Hindi speech, studies were reported (other than the
ones reported in this thesis) on the use of prosodic knowledge in the form of pitch
variations to hypothesise word boundaries [Madhukumar 1993; Rajendran and
Yegnanarayana 19941. The technique is described later in chapter 6 where its
performance is studied and several modifications are made by us to improve its
performance.
2.4 Summary and Conclusions
In this chapter a review of the studies conducted on word boundary
hypothesisation and its significance in speech recognition was presented. From these