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. Author manuscript; available in PMC: 2014 Jun 1.
Published in final edited form as: J Speech Lang Hear Res. 2013 Jun;56(3):1035–1044. doi: 10.1044/1092-4388(2012/12-0067)

Appendix B.

Coding Strategy

Coding Type Data Format Rationale Procedure
Video Code Video clips To quantify the perception of real-time facial expressions Coders viewed each 3–5second clip representing a single emotion and provided codes for overall impression of emotion type, expressiveness, and naturalness at clip conclusion (see Table 2). We did not ask coders to explain which specific features of the expressions related to their codes, so we could capture their most immediate and instinctual responses. Coders viewed clips with sound turned off.
Video code Audio files To quantify the perception of real-time prosody productions Same procedure as video coding of faces. Coders listened to clips without viewing the screen.
Freeze- frame code Video clips To capture the fine-grain distinctions and features that represent the component parts of dynamic facial expressions “Froze” video playback on the first frame of each clip, the frame at each subsequent second, and the final frame. Selected frames (roughly 4% of overall video frames) were coded for expressiveness, and naturalness. We did not include analysis of emotion type for this coding technique. Freeze-frames in a given clip tended to obtain different emotion type codes. Resulting data could not be suitably summarized and are therefore not included here. Coders who performed freeze-frame coding on a given participant did not also perform video coding on the same participant.
Acoustic Analysis Audio files To capture the fine-grain distinctions and features that represent the component parts of prosodic productions Used PRAAT (Boersma & Weenink, 2009) to record:
  • minimum fundamental frequency (F0)

  • maximum F0

  • mean F0

  • pitch range (max F0 – min F0)

  • minimum intensity

  • maximum intensity

  • mean intensity

  • intensity range (max intensity – min intensity).