1. [kmpjuteynl] [fownldi]
Speech Recognition
And
Text-to-Speech Systems

2. Phonology Phonetic alphabets Phonological rules
Computational Phonology
Phonological Learning
Optimality Theory

3. Phonetics Study of the pronunciation of words
Words are strings of symbols which represent phones
Can also include prosody

4. Phonetic Alphabets International Phonetic Alphabet (IPA)
Evolving standard since 1888
Goal is to be able to transcribe the sounds of all human languages

5. Phonetic Symbols ARPAbet IPA Specifically for American English
can be used where non-ASCII fonts are inconvenient (such as in online pronunciation dictionaries)
IPA
International Phonetic Alphabet
Evolving standard since 1988
Goal is to be able to transcribe sounds of all human languages

6. Phonological Rules Not all [t]s are created equally
Phones are pronounced differently in different contexts (phoneme vs. allophone)
e.g. [t] in tunafish is aspirated
e.g. [t] in starfish (following initial s) is unaspirated
Broad transcription vs. narrow transcription

7. Phonological Rules t d { }
 [ ] / V__V
ladder
lotus

8. Two-Level Morphology Koskenniemi (1983)
Most phonological rules are independent
Feeding and bleeding relations are rare
Explicitly code when rule is obligatory or optional
Rule type
Interpretation
a:b  c ___ d
a is always realized as b in the context c ___ d
a:b  c ___ d
a may be realize as b only in the context c ___ d
a:b  c ___ d
a must be realized as b in the context c ___ d and nowhere else
a:b /  c ___ d
a is never realized as b in the context c ___ d

9. Optimality Theory (OT)
Prince and Smolensky, 1993
Is a Connectionist theory of language
Views phonological derivation based on:
Two functions (GEN and EVAL) and
A set of ranked violable constraints (CON)
Assumed to be cross-linguistic generalizatoins

10. Optimality Theory (OT)
Given underlying form:
GEN function produces all imaginable surface forms
EVAL function then applies each constraint in CON to these surface forms in order of constraint rank

11. Optimality Theory (OT)
Constraints
Faithfulness (checks how faithful the surface form is to the underlying form)
e.g. FaithV—says “Don’t delete or insert vowels”
e.g. FaithC—says “Don’t delete or insert consonants”
Markedness (imposes requirements on the structural well-formedness of the output)
e.g. *Complex –says “no complex onsets or codas”

12. Optimality Theory (OT)
Uses constraints to filter out unneeded surface forms
Some constraints are more important than others

13. Optimality Theory (OT)
Can OT be implemented by finite-state transducers?
Is essential to enforce constraint only if does not reduce possibilities to zero

14. Optimality Theory (OT)
Ordinal OT grammars
Tesar & Smolensky (1998)
No absolute ranking values
i.e. they accepted only an ordinal relation between the constraint rankings
learning algorithm (Error-Driven Constraint Demotion, EDCD)
changes the ranking order whenever the form produced is different from the adult form
Fast and convergent, but extremely sensitive to errors in the learning data

15. Optimality Theory (OT)
Stochastic OT grammars
Boersma (1997b) / Boersma (1998) / Boersma (2000)
every constraint has a ranking value along a continuous ranking scale
a small amount of noise is added to this ranking value at evaluation time
associated error-driven learning algorithm (Gradual Learning Algorithm, GLA) effects small changes in the ranking values of the constraints with every learning step
can learn languages with optionality and variation

16. SIGMORPHON
ACL Special Interest Group on Computational Morphology and Phonology (SIGMORPHON)
formerly known as the ACL Special Interest Group on Computational Phonology (SIGPHON )
Recent research developments
Matters of interest in computational phonology and morphology