1. OPTIMAL TEXT SELECTION ALGORITHM ASR Project Meetings Dt: 08 June 2004 - Rohit Kumar - LTRC, IIIT Hyderabad

2. OPTIMAL TEXT SELECTION ALGORITHM Basic Greedy Algorithm 1.Get the Frequency Distribution of basic units in a language by analyzing a large corpus 2.Iterate for as many sentence as you want to select 1.For Each Sentence on the Corpus Score the sentence for its desirability in Optimal Text 2.Choose the sentence with best score into Optimal Text 3.Delete Selected Sentence from Corpus 4.Update the frequency distribution based on the sentence selected

3. OPTIMAL TEXT SELECTION ALGORITHM Text Corpus Phonetizer Syllabifier This Gives you a sequence of phonemes Basically a set of sentences This Gives you a sequence of basic units Diphone, Triphones, Syllables … Unit Distribution Analysis Counts the number of occurrences of each basic unit Corpus Frequency Distribution Analysis Step Unit Frequency ka10000 ek8756 ne6593 …

4. OPTIMAL TEXT SELECTION ALGORITHM Sentence Phonetizer Syllabifier This Gives you a sequence of phonemes This Gives you a sequence of basic units Diphone, Triphones, Syllables … Corpus Frequency Distribution How to Score each Sentence 1. Each units is scored on the basis of its desirability. 2. Desirability is proportional to Frequency of the unit in large corpus 3. Sentence Score = Sum of Fn(Score of all units in the sentence) / Number of Units Ranking Algorithm Scoring Function could either be linear or Inverse function

5. OPTIMAL TEXT SELECTION ALGORITHM Sentence Phonetizer Syllabifier This Gives you a sequence of phonemes This Gives you a sequence of basic units Diphone, Triphones, Syllables … Sentence Level Unit Frequency Distribution How to Update the Frequency Distribution Unit Distribution Analysis Counts the number of occurrences of each basic unit Corpus Frequency Distribution For Each Unit in Sentence Frequency Distribution, Subtract Modify its corpus frequency by K x (Frequency of Unit in Sentence) Modified Corpus Frequency Distribution

6. OPTIMAL TEXT SELECTION ALGORITHM Issues 1.Complete Desirable Coverage will not be possible with one step simple selection as it will bring a large number of sentences into the optimal text. “Optimal Text means Maximum Coverage and Minimum Size” How to Solve Follow multiple small steps as described ahead

7. OPTIMAL TEXT SELECTION ALGORITHM Our Strategy for Optimal Text Selection 1. From the large database, filter out sentences that are not of length between 5 to 15 words 2. From the frequency analysis of the unit, choose a set of N units (out of total M units), whose frequency is higher than a threshold (say around above 100). 3. Select the sentences (say X) which cover these N units 4. Repeat the process again with P (P = M - N) units – but restrict the number of sentences to be not more than 2 * X 5. For all the remaining units, select words which cover these units

8. OPTIMAL TEXT SELECTION ALGORITHM Phonetizer: A class that takes as input a text and gives as output a sequence of phonemes. What Phonemes ?? We will be following ITrans-3 as the notation across all our work. WordItrans – 3Phonemes namastenamasten, a, m, a, s, t, e dhanywaddhanywaaddh, a, n, y, w, aa, d textilet’ekstaailt’, e, k, s, t, aa, i, l khabreinqhabren’qh, a, b, r, e, n’ krishnakrxshhnaak, rx, shh, n, aa

9. OPTIMAL TEXT SELECTION ALGORITHM Class Details 1.Class constructor 2.AddText (inputs string, no output) 3.GetPhoneme (no input, outputs one phoneme) 4.IsEmpty (no input, outputs flag if no text to work on left) 3 is the phonetizing function which breaks a text into phonemes and will broadly be the same of all languages. The list of phonemes is shown in the next slide

10. OPTIMAL TEXT SELECTION ALGORITHM Phoneme list (for hindi, minor modifications for other languages) a a1 aa aa* aa1 i ii u uu e e* e1 ai o au n' : *' * rx lx rxx lxx k kh g gh ng- ch chh j jh nj- t' t'h d ' d'h nd- t th d dh n n~ p ph b bh m y r r~ l l' l'~ v sh shh s s- h q qh gx z dr~ dd~ f y~

11. OPTIMAL TEXT SELECTION ALGORITHM Handling English Words 1.Dictionary Lookup 2.Letter to Sounds Module

12. OPTIMAL TEXT SELECTION ALGORITHM Implementation: Syllabifier Basic Units: Diphones (2 phones), Triphones (3 phones), Syllables Basically takes the phonemes from Phonetizer and gives units. So if we are working with triphones t’, e, k, s, t, aa, i, l >> t’-e-k, e-k-s, k-s-t, s-t-aa, t-aa-i, aa-i-l Class Details 1. Class constructor 2. AddPhoneme (inputs a string, no output) 3. GetUnit (no input, outputs one string) 4. IsEmpty (no input, outputs flag if no phonemes left)

13. OPTIMAL TEXT SELECTION ALGORITHM Effort for each Language 1. Collect the Corpus (most of Hindi, Telugu, Tamil, Marathi already available) 2. Automatic Cleaning and Conversions on the Corpus * English Word to ITrans Conversion by dictionary lookup 3. Modifying the Phonetizer (and Syllabifier) for the language 4. Running the OTS strategy 5. Manually Checking Selected Corpus and Corrections 6. Optional: Reiterating 1 or more steps in OTS Strategy if need be