Aubanel, V. & Nguyen, N. (2010). Automatic recognition of regional phonological variation in conversational interaction. Speech Communication, 52, 577 – 586.
Presentation: Chris
Summary: Shelly
There is a growing interest in finding out the impact of dialectal variation on speech communication. The present study aimed to explore this issue by investigating the possible dialectal interaction in spontaneous conversion, with a focus on two major varieties of French, Northern French (NF) and Southern French (SF). An interactive task GMUP (Group’em up!) was designed, which is a collaborative game targeted to lead participants to spontaneously produce purpose-built names. In those names, five phonological dimensions were embedded, on which well-known differences between NF and SF exist: (1) word-final schwa realization in SF, (2) back mid vowel fronting in NF, (3) the contrast between mid-high and mid-low vowels in NF, (4) affrication of coronal stops in SF, and (5) the nasal vowel shift in NF. They recorded 12 dyads of one NF speaker and one SF speaker. The authors attempted to see whether the above five dimensions were distinctive enough for their Bayes classifier to determine the regional dialects of speakers, and whether speaker accommodation took place through out the game. That is, whether differences between NF and SF speakers would be mitigated throughout the game. Results showed that Byes classifier achieved a 79% recognition rate based on the five dimensions, suggesting that the developing classifier is quite good, and the above five dimensions are workable indicators on machines for differentiating the two dialects. However, such a high recognition rate did not decrease as the interaction between participants proceeded, meaning that speaker convergence did not happen. One possibility might be that the convergence took place at a subcategorical level, which their classifier was not sensitive enough to capture. Further studies will be needed to find out whether there are dialectal convergences throughout conversation at a more fine-grained level.
There is a growing interest in finding out the impact of dialectal variation on speech communication. The present study aimed to explore this issue by investigating the possible dialectal interaction in spontaneous conversion, with a focus on two major varieties of French, Northern French (NF) and Southern French (SF). An interactive task GMUP (Group’em up!) was designed, which is a collaborative game targeted to lead participants to spontaneously produce purpose-built names. In those names, five phonological dimensions were embedded, on which well-known differences between NF and SF exist: (1) word-final schwa realization in SF, (2) back mid vowel fronting in NF, (3) the contrast between mid-high and mid-low vowels in NF, (4) affrication of coronal stops in SF, and (5) the nasal vowel shift in NF. They recorded 12 dyads of one NF speaker and one SF speaker. The authors attempted to see whether the above five dimensions were distinctive enough for their Bayes classifier to determine the regional dialects of speakers, and whether speaker accommodation took place through out the game. That is, whether differences between NF and SF speakers would be mitigated throughout the game. Results showed that Byes classifier achieved a 79% recognition rate based on the five dimensions, suggesting that the developing classifier is quite good, and the above five dimensions are workable indicators on machines for differentiating the two dialects. However, such a high recognition rate did not decrease as the interaction between participants proceeded, meaning that speaker convergence did not happen. One possibility might be that the convergence took place at a subcategorical level, which their classifier was not sensitive enough to capture. Further studies will be needed to find out whether there are dialectal convergences throughout conversation at a more fine-grained level.
