In spontaneous speech, emotion information is embedded at several levels: acoustic, linguistic, gestural (non-verbal), etc. For emotion recognition in speech, there is much attention to acoustic level and some attention at the linguistic level. In this study, we identify paralinguistic markers for emotion in the language. We study two Indian languages belonging to two distinct language families...

Prior research on gaze, turn-taking, and backchannels suggests that the speaker’s gaze cues the listener’s paralinguistic responses, including feedback behaviors. To explore how conversants use feedback cues and responses, I studied a corpus of face-to-face conversational interaction, primarily using a conversation-analytic approach. Analysis of the dialogs suggests that paralinguistic behavior...

Prosody fulfills a variety of functions in dialogues. Our study examines the relationship between different levels of perceived prominence of syllables and the linguistic and paralinguistic categories accent and emphasis which are conveyed prosodically. It is still unclear, how a notational system might look like that is able to capture the fine–grained differences between both. The notion of p...

This paper deals with the role of paralinguistic expression in articulatory speech synthesis. We describe two experiments which investigate the perception of certain vs. uncertain utterances produced by articulatory speech synthesis, using the system developed in [1]. Experiment 1 tests to what extent subjects are able to identify certainty and uncertainty as intended paralinguistic expressions...

The present study examines the coordination of lexical and paralinguistic F0 in second language (henceforth L2) production. We tested how L2 learners manage to handle F0 when F0 in their first language (henceforth L1) carries a paralinguistic function, but a lexical one in their L2 and vice versa. Participants (fifteen L1 Japanese speakers and fifteen L1 German speakers, proficient also in thei...

Humans perceive emotion from each other using a holistic perspective, accounting for diverse personal, non-emotional variables, such as age and personality, that shape expression. In contrast, today’s algorithms are mainly designed to recognize in isolation, usually demonstrated only within one relatively narrow database. this article, we propose multi-task learning approach jointly learn the r...