  Speech emotion recognition (SER) is vital for obtaining emotional
intelligence and understanding the contextual meaning of speech. Variations of
consonant-vowel (CV) phonemic boundaries can enrich acoustic context with
linguistic cues, which impacts SER. In practice, speech emotions are treated as
single labels over an acoustic segment for a given time duration. However,
phone boundaries within speech are not discrete events, therefore the perceived
emotion state should also be distributed over potentially continuous
time-windows.
  This research explores the implication of acoustic context and phone
boundaries on local markers for SER using an attention-based approach. The
benefits of using a distributed approach to speech emotion understanding are
supported by the results of cross-corpora analysis experiments. Experiments
where phones and words are mapped to the attention vectors along with the
fundamental frequency to observe the overlapping distributions and thereby the
relationship between acoustic context and emotion. This work aims to bridge
psycholinguistic theory research with computational modelling for SER.
