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

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3.3.2 Results of lexical analysk with approximate matching The results of lexical analysis when exact matching was used, show that on the average 120 word sequences match a given sentence. However this number will increase if one allows errvrs in the inpiit sentence as in a phoneme sequence produced by a speech signal-to-symbol conversion stage. The errors can be: (i) substitution errors, where an input phoneme was rnisrecognised as another phoneme, (ii) insertion errors, where a new phoneme was inserted in input sequence, and (iii) deletion errors, where a phoneme was missed out during recognition. In this study, only substitution errors are considered as these are more frequent and can be characterised easily. Such errors are handled in the lexical analysis by using approximate matching instead of exact matching with the lexicon. In the approximate matching, all word strings that match the input phoneme string within a specified mismatch cost are generated. If the mismatch cost is larger than the total errors in the input sentence, then the uttered sentence will also be generated by the lexical analyser. However, many other word strings may also be produced in this process. The lexical analyser program was run again with an input text containing 10 sentences. The sentences were of varying lengths and contained between 25 to 45 phonemes. All word boundaries were removed from them. The lexical matching algorithm described earlier was used to match these sentences against the lexicon. The maximum mismatch between the input and the hypothesised word string was varied from 0 to 5. The results, in terms of the number of alternate word strings, are shown in Table - 3.3. Since a sentence on the average contained 35 phonemes, a variation in mismatch from 0 to 5 represented a variation in the input error from 0 to 12%. However in a speech recognition system, errors in the speech signal-to-symbol conversion may sometimes be as large as 50%. But the error variation in our studies
Match < Sentence nunber cost 1 2 3 L 5 6 7 8 9 10 Table-3.3 The no. of alternate word strings matching a sentence without word boundaries when approximate matching is used. Results are shown for 10 sentences at varying matching costs.
Page 1 and 2: Dr. €3. YEGNANARAYANA Professor D
Page 3 and 4: ACKNOWLEDGEMENTS I thank my researc
Page 5 and 6: -3 SIGNIFICANCE OF WORD BOUNDARIES
Page 7 and 8: 6.6 Location of word boundaries fro
Page 9 and 10: ABSTRACT This thesis addresses the
Page 11 and 12: \ known. The lexical analyser can n
Page 13 and 14: alounddhelongtableheagsnoddedenunis
Page 15 and 16: word boundaries into a text with wo
Page 17 and 18: words. The idea is to spot symbol s
Page 19 and 20: F1 position at a vowel-consonant bo
Page 21 and 22: -a2 A REVIEW OF THE STUDIES ON, WOR
Page 23 and 24: 1. When a midclass representation w
Page 25 and 26: particular interest is the performa
Page 27 and 28: was found that at broadclass level,
Page 29 and 30: in speaking rate indicate phrase bo
Page 31 and 32: y an estimator function E from the
Page 33 and 34: studies, the following issues are i
Page 35 and 36: 2. The effect of word boundary info
Page 37: * This selection can be done in man
Page 40 and 41: me : me:ra: metra: na: me:ra: na:m
Page 42 and 43: No. of alternatives 0-10 10-100 100
Page 46 and 47: had to be restricted to the above r
Page 48 and 49: Match Sentence nunber cost 1 2 3 4
Page 50 and 51: Match Sentence nuher cost 1 2 3 4 5
Page 52 and 53: 6 10 Number of 10 a1 ternate word s
Page 54 and 55: lexlcal analysis Mismatch cost Fig.
Page 56 and 57: had all word boundaries, is plotted
Page 58 and 59: Watch Sentence number cost 1 2 3 4
Page 60 and 61: Time lor lexical analysis 0 1 2 3 4
Page 62 and 63: Match Sentence tunter cost 1 2 3 4
Page 64 and 65: Time lor lexical analysis 1 0 1 2 3
Page 66 and 67: speech recognition process. On the
Page 68 and 69: proposed clues are based on the obs
Page 70 and 71: Case Markers: Pronouns : ka:, ki:,
Page 72 and 73: form. The above Hindi text was corr
Page 74 and 75: that if there are some substitution
Page 76 and 77: These measures were defined as foll
Page 78 and 79: Case Conjunc- Pronouns Verb Aux . A
Page 80 and 81: - I-' X Error in input text X Error
Page 82 and 83: % Error Fig.4.4 Results of word bou
Page 84 and 85: % Error Fig.4.5 A comparison of the
Page 86 and 87: 0 I 1 I 0 10 20 30 40 50 60 % Error
Page 88 and 89: 60 4 0 No. of subsentences No. of s
Page 90 and 91: LC1: A Hindi word can end either in
Page 92 and 93: Fig.4.10 along with the results for
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oundaries spotted) against system s
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from other words, such as 'national
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dictionary contained nearly 30000 w
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Vowel sequences Consonant sequences
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VC' were considered. It can be obse
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percentage of incorrect hypotheses
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% Error in input text 0 10 20 30 40
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% Error Fig.5.1 Results of word bou
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hypotheses produced by the lexical
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transformed into other nonword-inte
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WB hyp. errors 300 - 200 - ( v+> 10
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number of incorrect hypotheses will
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I--- Correctness 60 8o lmprovement
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% Error in input text 10 20 30 40 5
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will be smaller and hence S and P(y
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word boundary is within the consona
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clues except for clues of types CV'
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Pauses in speech, though small in n
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Several studies on English speech s
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Speaker VB hypotheses at various th
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Speaker UF hypotheses at various th
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Speaker UF hypotheses at various th
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Fig.6.1 The plot of pitch frequency
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From the results, it can be seen th
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speakers, with the incorrect hypoth
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durational effects. One possible ex
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From these results, it can be seen
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shown that the prosodic features of
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chapter 7 WORD BOUNDARY CLUES BASED
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consonants. Thus one can consider o
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Speaker VB hypotheses(VB:&) at vari
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Speaker UF hypotheses(UF:UI) at var
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Speaker UB hypotheses(UB:B) at vari
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high speaking rates. This is also b
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vowels preceding word boundaries, i
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word-final vowels than word-interna
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8.1 Introduction PERFORMANCE OF WOR
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Match Sentence nunber, cost 1 2 3 4
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75 Reduction in the time for lexica
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The reduction in the lexical analys
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Hatch Sentence nuher cost 1 2 3 4 5
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Chapter 9 SUMMARY AND CONCLUSIONS I
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In the last study (described in cha
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the language and lexical clues are
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REFERENCES Baken R.J. and Daniloff
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Cutler A. and Butterfield S. (199lb
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Prakash M., Ramana Rao G,V., Chandr
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Zelenski R. and Class F. (1983), A
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