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-- A corpus study using logistic regression Yao 1 Vowel alternation in the pronunciation of THE in American English.

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Presentation on theme: "-- A corpus study using logistic regression Yao 1 Vowel alternation in the pronunciation of THE in American English."— Presentation transcript:

1 -- A corpus study using logistic regression Yao Yao @NWAV37 1 Vowel alternation in the pronunciation of THE in American English

2 B ACKGROUND How do you say the word THE ? [dh ah], with a schwa [dh iy], with a high front tense vowel What is the rule for vowel alternation? Canonical rule: [dh iy] / _ [+vowel] [dh ah ] / otherwise Other stories? 2

3 B ACKGROUND Age (Keating et al, 1994) TIMIT Corpus of read speech in English Age-dependent pronunciation 3 Younger speakers have a higher probability of using other vowels than [iy] in “the” before vowel. No speakers above 50 yrs use other vowels than [i] before vowels.

4 B ACKGROUND Disfluency (Fox Tree & Clark, 1997) More [dh iy] (81%) than [dh ah] (7%) before suspension of speech. Ongoing sound change Age Gender? Social class? Dialect? Online speech production Planning problem Speech rate? 4

5 D ATA Buckeye corpus 40 speakers All residents at Columbus, Ohio Balanced in age and gender 1-hr interview Transcribed at word and phone level Dataset All tokens of the from all speakers 5

6 P RELIMINARY COUNTS 8132 instances of the 172 different phonetic transcriptions 10 most common pronunciation cover 84.19% of the tokens Most common syllable structures CV (N=7003); V (N=913); C (N=164) Most common vowels [ah] (N=4426); [ih] (N=1808); [iy] (N=1130) 6 At least three vowel variants, instead of two!

7 P RELIMINARY ANALYSIS Vowel name and duration [ ə ] [ ɪ ] [i] 7

8 P RELIMINARY ANALYSIS General vowel alternation pattern regarding the following segment 8

9 S TUDY DESIGN Use logistic regression to model the alternation among the three vowels ([ ah ], [ ih ], [iy]). Predictor variables include phonological factor: following segment speaker characteristics: age, gender contextual features: disfluency, speech rate 9

10 C ODING VARIABLES Vowel variant (outcome variable) ah: [ ə ] ih: [ ɪ ] Iy: [i] Following segment C: Consonant V: Vowel U: Non-lingusitic Age Y: Young (<40 yr) O: Old (>=40 yr) 10

11 C ODING VARIABLES ( CONT ’ D ) Gender F: Female M: Male Following Disfluency D: Disfluent Pause Filled pause ( um, uh, you know). Repetition ( the) Hesitation, cutoff, extended pronunciation F: Fluent otherwise 11

12 C ODING VARIABLES ( CONT ’ D ) Preceding Disfluency D: Disfluent Similar to following disfluency F: Fluent Speed Average speed of the pause-bounded stretch (in # of syll per second) 12

13 S IMPLEST MODEL [ah] vs. [iy] Exclude cases followed by non-linguistic sounds. 5046 cases remain. Predictor variables Block 1: following segment Block 2: age, gender, and their interaction with following segment Block 3: speed, presence of disfluency, and their interaction with other variables Method = Forward stepwise (conditional) 13

14 S IMPLEST MODEL ( CONT ’ D ) Results Following segment is most significant. Percentage of right prediction: 80.3%  90.6% Following disfluency is also significant. No other factor or interaction appears significant. Temporary conclusion Old/young male/female speakers respect the canonical phonological rule equally well. 14

15 ABOUT [ IH ] Some basic facts Women produce [ih] more often than men (28.2% vs. 21.3%) Young people produce [ih] more often than older people (23.3% vs. 26.1%) The majority are followed by consonants (84.5%). Are these also the factors that would favor [ih] over [ah] or [iy]? 15

16 A TAD MORE COMPLICATED : [ IH ] VS. [ IY ] Exclude cases followed by non-linguistic sounds. 2675 cases remain. Same independent variables as the previous model Results Following segment is the most significant condition (right prediction: 62.8%  80.7%) Following disfluency is also significant (80.7%  81.4%) Other significant factors: gender, gender X following segment, speed X following segment 16

17 [ IH ] VS. [ AH ] Exclude cases followed by non-linguistic sounds. 5747 cases remain. Same independent variables as the previous model Results Following segment is still significant, but the significance is reduced (right prediction: 70.8%  71.5%) Other significant factors: gender X following segment, age, age X gender, following disfluency 17

18 T EMPORARY CONCLUSIONS Most important factor is following segment, but the effect is weakest in the ah/ih model. The presence of following disfluency also affects vowel alternation consistently, and the effect is strongest in iy/ih alternation. 18

19 E FFECT OF FOLLOWING DISFLUENCY IN IH / IY COMPARISON 19 Speaker characteristics (age, gender) and speech rate fail to enter the model for ah/iy distinction, but do show in the other two models considering the [ih] vowel. In particular, the interaction of gender and following segment shows in both models.

20 M OVING ON TO CASES FOLLOWED BY NON - LINGUISTIC SOUNDS [ah] vs. [iy] Same model, but with all cases (N=5556) Significant factors Block 1: Following segment (79.7%  89.0%) Block 2: Age X following segment, age, age X gender. Block 3: Following disfluency, speed and their interaction. Speed X following segment. (89.0%  89.3%) 20

21 M OVING ON TO CASES FOLLOWED BY NON - LINGUISTIC SOUNDS [ih] vs. [iy] Same model, but with all cases (N=2938) Significant factors Block 1: Following segment (61.5%  78.1%) Block 2: age, gender, age X following segment, gender X following segment. (78.1%  79.1) Block 3: Following disfluency, speed and their interaction. (79.1%  80.7%) 21

22 M OVING ON TO CASES FOLLOWED BY NON - LINGUISTIC SOUNDS [ah] vs. [ih] Same model, but with all cases (N=6234) Significant factors Block 1: Following segment (71.0%  71.6%) Block 2: age, gender, age X gender. (71.6%  71.7%) Block 3: Following disfluency X speed. 22

23 T EMPORARY CONCLUSIONS When all cases are included (followed by consonant, vowel, or non-linguistic sounds) Speaker characteristics enter the models, even the one for ah/iy distinction. Following disfluency and speed continue to contribute in all models. The ah/ih distinction is still the hardest to model. 23

24 E FFECT OF G ENDER 24

25 E FFECT OF AGE 25

26 G ENERAL DISCUSSION Ongoing sound change? - Yes… The new pronunciation [dh ih] A variant form of [dh ah]? Speaker characteristics at play? What about elongated [dh ah]? A variant form of [dh iy]? Vowel alternation  duration alternation? Disfluency and speech rate affecting the pronunciation? - Yes… Following (un)filled pauses and repetition Preceding disfluency has no effect 26

27 N EXT STEP Examine the phonetic makeup of the vowels Moving from modeling vowel name distinction to modeling continuous variables, such as formants and durations Include more speaker variables More specific age variable Social class? Include more contextual measures More types of disfluency Contextual predictability? 27

28 T HANKS ! Questions and comments are more than welcome… 28

29 R EFERENCES Fox Tree, J.E., Clark, H.H. (1997). Pronouncing "the" as "thee" to signal problems in speaking. Cognition, 62, 151-167 Keating, P., MacEachern, M., Shryock, A., Dominguez, S. (1994). A manual for phonetic transcription: Segmentation and labeling of words in spontaneous speech. Manual written for the Linguistic Data Consortium, UCLA Working Papers in Phonetics 88, 91-120 Pitt, M.A., Dilley, L., Johnson, K., Kiesling, S., Raymond, W., Hume, E. and Fosler-Lussier, E. (2007) Buckeye Corpus of Conversational Speech (2nd release) [www.buckeyecorpus.osu.edu] Columbus, OH: Department of Psychology, Ohio State University (Distributor). 29


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