The Emotion Markup Language EmotionML is, as of October 2010, a public Working Draft at the W3C.

The SEMAINE API is one of the first pieces of software to implement EmotionML. It is our intention to provide an implementation report as input to the W3C standardisation process in due course, highlighting any problems encountered with the current draft specification in the implementation.

EmotionML aims to make concepts from major emotion theories available in a broad range of technological contexts. Being informed by the affective sciences, EmotionML recognises the fact that there is no single agreed representation of affective states, nor of vocabularies to use. Therefore, an emotional state<emotion>can be characterised using four types of descriptions: <category>, <dimension>, <appraisal> and <action-tendency>. Furthermore, the vocabulary used can be identified. The EmotionML markup the example on the EMMA page uses a dimensional representation of emotions, using the dimension set “FSRE.xml”, out of which two dimensions are annotated: arousal and valence.

EmotionML is aimed at three use cases: 1. Human annotation of emotion-related data; 2. automatic emotion recognition; and 3. generation of emotional system behaviour. In order to be suitable for all three domains, EmotionML is conceived as a “plug-in” language that can be used in different contexts. In the SEMAINE API, this plug-in nature is applied with respect to recognition, centrally held information, and generation, where EmotionML is used in conjunction with different markups. EmotionML can be used for representing the user emotion currently estimated from user behaviour, as payload to an EMMA message. It is also suitable for representing the centrally held information about the user state, the system's “current best guess” of the user state independently of the analysis of current behaviour. Furthermore, the emotion to be expressed by the system can also be represented by EmotionML. In this case, it is necessary to combine EmotionML with the output languages FML, BML and SSML.

Last modified 11 years ago Last modified on 12/14/10 19:15:59