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

2. Lexical match was performed at each syllable, which means that a word boundary
was assumed after every syllable.
3. Lexical match was initiated at the beginning of the sentence and subsequently at the
conclusion of each successful lexical match. This strategy was used in most speech
recognition systems [Cole and Jakimik 19801.
4. Lexical match was initiated at each strong syllable. This strategy was based on the
Metrical. Segmentation Strategy(MSS) suggested for English [Cutler and Carter 19871.
Thus, in this strategy, information regarding word boundaries was used in matching.
The above four lexical match strategies were compared on three types of input
representation of increasing complexity, namely, (a) A sentence represented as a
sequence of phonemes, (b) a sentence transcribed such that the strong syllables were
transcribed exactly whereas the weak syllables were transcribed into their broadclass
categories, and (c) a sentence transcribed such that the strong syllables were
transcribed into their midclass categories and the weak syllables into their broadclass
categories. Thus the above three types of inputs were of increasing complexity. The
results of the study were as follows:
1. For input type (a), Strategies 1 and 2 produced more matching word sequences than
strategies 3 and 4, as expected.
2. For input types (b) and (c), strategy 1 again produced the highest number of
matching word sequences. But unlike the earlier case, strategy 2 performed better than
strategy 3 in that it produced less number of matching word sequences. Strategy 4
performed best by producing the least number of matching word sequences.
The above results established that knowledge of the word boundaries (even if it
is only partial as in strategy 2) can improve the performance of the lexical match,
especially when the input is only partially known (midclass or broadclass strings). Of