Paralinguistics in speech and language - State-of-the-art and the challenge

By Björn Schuller, Stefan Steidl, Anton Batliner, Felix Burkhardt, Laurence Y. Devillers, Christian A. Müller, Shrikanth S. Narayanan. 2013

343 citations recorded by the source corpus.

Paralinguistic analysis is increasingly turning into a mainstream topic in speech and language processing. This article aims to provide a broad overview of the constantly growing field by defining the field, introducing typical applications, presenting exemplary resources, and sharing a unified view of the chain of processing. It then presents the first broader Paralinguistic Challenge organised at INTERSPEECH 2010 by the authors including a historical overview of the Challenge tasks of recognising age, gender, and affect, a summary of methods used by the participants, and their results. In addition, we present the new benchmark obtained by fusion of participants' predictions and conclude by discussing ten recent and emerging trends in the analysis of paralinguistics in speech and language.

Subfields: Experimental and Cognitive Psychology

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In Experimental and Cognitive Psychology

Citations in the corpus

Generative Spoken Dialogue Language Modeling (2022, background): “However, all the progress in this research work centered around text dialogues leaving out non-lexical information (Schuller et al., 2013; Ang et al., 2002) in human-human dialogues, e.g., emotion, pauses, laughter, hesitation, and inter-ruption.”
The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism (2013, methodology): “With the INTERSPEECH’s 2009 Emotion Challenge [1], 2010 Paralinguistic Challenge [2], 2011 Speaker State Challenge [3], and the recent 2012 Speaker Trait Challenge [4] we organised challenges and official exchange fora as exist for many more ‘traditional’ speech tasks, comparable to the NIST evaluat”
Improving Speech Prosody of Audiobook Text-To-Speech Synthesis with Acoustic and Textual Contexts (2022, background): “Synthesizing such speech requires the system to not only transform linguistic information but also para-/non-linguistic information such as emotions, and intentions from text to speech [4, 5, 6].”
A Survey on perceived speaker traits: Personality, likability, pathology, and the first challenge (2015, background): “In 2009 to 2012, challenges (Schuller et al., 2009, 2010, 2011b, 2012, 2013a,b) were organised at the INTERSPEECH conferences that featured several different aspects of paralinguistics: topics of interest were not what the speaker said, i. e., word recognition, or the semantics behind word…”
A review of depression and suicide risk assessment using speech analysis (2015, background): “speaker recognition and other paralinguistic tasks, such as age and gender recognition (Schuller et al., 2013), when compared to the accuracy of many mental state systems it seems reasonable to assume depression and suicidality have a low degree of variability in speech i.”