One of the common ways that phoneticians and other researchers have looked at emotion-in-language is by studying acted affect. That is, you get a bunch of people to read number lists or the alphabet in “angry” voice, “happy” voice, etc. Then you see if other people can reliably guess the emotion and then you go and look for the acoustic correlates.
If you’re interested in this sort of thing, you could try the Emotional Prosody Speech and Transcripts corpus (if you’re at Stanford and you’ve gotten corpus access, you’ll find it at /afs/ir/data/linguistic-data/EmotionalProsodySpeechAndTranscripts).
Now, there are a number of known issues with acted data–which is that it is stereotyped in particular ways. And if you wanted to detect what’s going on in a call center, “angry actors” wouldn’t help you nearly as much as “actual callers who are annoyed/disappointed/etc”. If you’re curious about more naturalistic corpora/research, here are some resources you might find useful (they’re all on my web page about emotions and language: http://www.stanford.edu/~tylers/emotions.shtml).
- My talk at Nuance (the Dragon Naturally Speaking and Siri folks): http://www.stanford.edu/~tylers/notes/papers/emotion/Nuance_emotion_detection_11-17-10_final.pptx. This is basically an intro for dealing with naturalistic emotional data for speech scientists and others interested in detection/recongition.
- Notes on Clavel and Devillers (2011): http://www.stanford.edu/~tylers/notes/emotion/Comp_speech_special_issue_2011_reading_notes_Schnoebelen.pdf
- Notes on Cowie and Cornelius (2003): http://www.stanford.edu/~tylers/notes/emotion/Cowie_Cornelius_2003_reading_notes_Schnoebelen.pdf
- Maybe my notes on Amir and Cohen (2007) and a few others: http://www.stanford.edu/~tylers/notes/emotion/Various_detection_articles_reading_notes_Schnoebelen.pdf
- You might poke around http://emotion-research.net/ for some more naturalistic corpora that are being used by people interested in emotion research. (And let me know what you find that’s useful.)
11/7/2011 post-script: If acted data suits your needs, you can also consider something other than English–for example, the Mandarin Affective Speech corpus will get you Chinese.