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Found 15 papers, 9 papers with code
Exploring Transfer Learning for Low Resource Emotional TTS
During the last few years, spoken language technologies have known a big improvement thanks to Deep Learning.
The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation Systems
In this paper, we present a database of emotional speech intended to be open-sourced and used for synthesis and generation purpose.
A Transformer-based joint-encoding for Emotion Recognition and Sentiment Analysis
Understanding expressed sentiment and emotions are two crucial factors in human multimodal language.
Ranked #5 on
Multimodal Sentiment Analysis
on CMU-MOSEI
(using extra training data)
Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis
The field of Text-to-Speech has experienced huge improvements last years benefiting from deep learning techniques.
ICE-Talk: an Interface for a Controllable Expressive Talking Machine
ICE-Talk is an open source web-based GUI that allows the use of a TTS system with controllable parameters via a text field and a clickable 2D plot.
Analysis and Assessment of Controllability of an Expressive Deep Learning-based TTS system
In this paper, we study the controllability of an Expressive TTS system trained on a dataset for a continuous control.
Modulated Fusion using Transformer for Linguistic-Acoustic Emotion Recognition
This paper aims to bring a new lightweight yet powerful solution for the task of Emotion Recognition and Sentiment Analysis.
Ranked #6 on
Multimodal Sentiment Analysis
on CMU-MOSEI
(using extra training data)
Laughter Synthesis: Combining Seq2seq modeling with Transfer Learning
Despite the growing interest for expressive speech synthesis, synthesis of nonverbal expressions is an under-explored area.
MUST&P-SRL: Multi-lingual and Unified Syllabification in Text and Phonetic Domains for Speech Representation Learning
In this paper, we present a methodology for linguistic feature extraction, focusing particularly on automatically syllabifying words in multiple languages, with a design to be compatible with a forced-alignment tool, the Montreal Forced Aligner (MFA).
ASR-based Features for Emotion Recognition: A Transfer Learning Approach
During the last decade, the applications of signal processing have drastically improved with deep learning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Proceedings of eNTERFACE 2015 Workshop on Intelligent Interfaces
The 11th Summer Workshop on Multimodal Interfaces eNTERFACE 2015 was hosted by the Numediart Institute of Creative Technologies of the University of Mons from August 10th to September 2015.
A Methodology for Controlling the Emotional Expressiveness in Synthetic Speech -- a Deep Learning approach
The second step is the development of a system to automatically annotate data with emotion/expressiveness features.
The Theory behind Controllable Expressive Speech Synthesis: a Cross-disciplinary Approach
Finally, we focus on the last one, with the last techniques modeling Text-to-Speech synthesis as a sequence-to-sequence problem.
Where Is My Mind (looking at)? Predicting Visual Attention from Brain Activity
The codes and dataset considered in this paper have been made available at \url{https://figshare. com/s/3e353bd1c621962888ad} to promote research in the field.
Flowchase: a Mobile Application for Pronunciation Training
In this paper, we present a solution for providing personalized and instant feedback to English learners through a mobile application, called Flowchase, that is connected to a speech technology able to segment and analyze speech segmental and supra-segmental features.
