Guest Editorial: Special Issue on Affective Speech and Language Synthesis, Generation, and Conversion

Autor: Shahin Amiriparian, Bjorn W. Schuller, Nabiha Asghar, Heiga Zen, Felix Burkhardt
Rok vydání: 2023
Předmět:
Zdroj: IEEE Transactions on Affective Computing. 14:3-5
ISSN: 2371-9850
Popis: The papers in this special section focus on affective speech and language synthesis, generation, and conversion. As an inseparable and crucial part of spoken language, emotions play a substantial role in human-human and human-technology conversation. They convey information about a person’s needs, how one feels about the objectives of a conversation, the trustworthiness of one’s verbal communication, and more. Accordingly, substantial efforts have been made to generate affective text and speech for conversational AI, artificial storytelling, and machine translation. Similarly, there is a push for converting the affect in text and speech, ideally, in real-time and fully preserving intelligibility, e. g., to hide one’s emotion, for creative applications and in entertainment, or even to augment training data for affect analyzing AI.
Databáze: OpenAIRE