Gustav Eje Henter

DeepAI AI Chat

Featured Co-authors

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382 publications
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37 publications
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18 publications
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17 publications

research

∙ 09/06/2023

Matcha-TTS: A fast TTS architecture with conditional flow matching

We introduce Matcha-TTS, a new encoder-decoder architecture for speedy T...

0 Shivam Mehta, et al. ∙

research

∙ 08/24/2023

The GENEA Challenge 2023: A large scale evaluation of gesture generation models in monadic and dyadic settings

This paper reports on the GENEA Challenge 2023, in which participating t...

0 Taras Kucherenko, et al. ∙

research

∙ 07/11/2023

On the Use of Self-Supervised Speech Representations in Spontaneous Speech Synthesis

Self-supervised learning (SSL) speech representations learned from large...

0 Siyang Wang, et al. ∙

research

∙ 06/15/2023

Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis

With read-aloud speech synthesis achieving high naturalness scores, ther...

0 Shivam Mehta, et al. ∙

research

∙ 03/15/2023

Evaluating gesture-generation in a large-scale open challenge: The GENEA Challenge 2022

This paper reports on the second GENEA Challenge to benchmark data-drive...

0 Taras Kucherenko, et al. ∙

research

∙ 03/13/2023

A processing framework to access large quantities of whispered speech found in ASMR

Whispering is a ubiquitous mode of communication that humans use daily. ...

0 Pablo Pérez Zarazaga, et al. ∙

research

∙ 03/05/2023

A Comparative Study of Self-Supervised Speech Representations in Read and Spontaneous TTS

Recent work has explored using self-supervised learning (SSL) speech rep...

0 Siyang Wang, et al. ∙

research

∙ 01/24/2023

Context-specific kernel-based hidden Markov model for time series analysis

Traditional hidden Markov models have been a useful tool to understand a...

0 Carlos Puerto-Santana, et al. ∙

research

∙ 01/13/2023

A Comprehensive Review of Data-Driven Co-Speech Gesture Generation

Gestures that accompany speech are an essential part of natural and effi...

1 Simbarashe Nyatsanga, et al. ∙

research

∙ 11/24/2022

Prosody-controllable spontaneous TTS with neural HMMs

Spontaneous speech has many affective and pragmatic functions that are i...

0 Harm Lameris, et al. ∙

research

∙ 11/17/2022

Listen, denoise, action! Audio-driven motion synthesis with diffusion models

Diffusion models have experienced a surge of interest as highly expressi...

0 Simon Alexanderson, et al. ∙

research

∙ 11/13/2022

Autovocoder: Fast Waveform Generation from a Learned Speech Representation using Differentiable Digital Signal Processing

Most state-of-the-art Text-to-Speech systems use the mel-spectrogram as ...

0 Jacob J Webber, et al. ∙

research

∙ 11/13/2022

OverFlow: Putting flows on top of neural transducers for better TTS

Neural HMMs are a type of neural transducer recently proposed for sequen...

0 Shivam Mehta, et al. ∙

research

∙ 09/22/2022

Predicting pairwise preferences between TTS audio stimuli using parallel ratings data and anti-symmetric twin neural networks

Automatically predicting the outcome of subjective listening tests is a ...

0 Cassia Valentini-Botinhao, et al. ∙

research

∙ 08/22/2022

The GENEA Challenge 2022: A large evaluation of data-driven co-speech gesture generation

This paper reports on the second GENEA Challenge to benchmark data-drive...

8 Youngwoo Yoon, et al. ∙

research

∙ 02/22/2022

Wavebender GAN: An architecture for phonetically meaningful speech manipulation

Deep learning has revolutionised synthetic speech quality. However, it h...

0 Gustavo Teodoro Döhler Beck, et al. ∙

research

∙ 08/30/2021

Neural HMMs are all you need (for high-quality attention-free TTS)

Neural sequence-to-sequence TTS has achieved significantly better output...

0 Shivam Mehta, et al. ∙

research

∙ 08/25/2021

Integrated Speech and Gesture Synthesis

Text-to-speech and co-speech gesture synthesis have until now been treat...

0 Siyang Wang, et al. ∙

research

∙ 08/12/2021

Multimodal analysis of the predictability of hand-gesture properties

Embodied conversational agents benefit from being able to accompany thei...

0 Taras Kucherenko, et al. ∙

research

∙ 07/01/2021

Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainability

In pursuit of explainability, we develop generative models for sequentia...

0 Anubhab Ghosh, et al. ∙

research

∙ 06/28/2021

Speech2Properties2Gestures: Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech

We propose a new framework for gesture generation, aiming to allow data-...

0 Taras Kucherenko, et al. ∙

research

∙ 06/25/2021

Transflower: probabilistic autoregressive dance generation with multimodal attention

Dance requires skillful composition of complex movements that follow rhy...

2 Guillermo Valle Pérez, et al. ∙

research

∙ 06/03/2021

The Case for Translation-Invariant Self-Attention in Transformer-Based Language Models

Mechanisms for encoding positional information are central for transform...

0 Ulme Wennberg, et al. ∙

research

∙ 02/23/2021

A large, crowdsourced evaluation of gesture generation systems on common data: The GENEA Challenge 2020

Co-speech gestures, gestures that accompany speech, play an important ro...

0 Taras Kucherenko, et al. ∙

research

∙ 02/15/2021

Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flows

We test the robustness of a maximum-likelihood (ML) based classifier whe...

0 Anubhab Ghosh, et al. ∙

research

∙ 01/28/2021

HEMVIP: Human Evaluation of Multiple Videos in Parallel

In many research areas, for example motion and gesture generation, objec...

0 Patrik Jonell, et al. ∙

research

∙ 01/14/2021

Generating coherent spontaneous speech and gesture from text

Embodied human communication encompasses both verbal (speech) and non-ve...

0 Simon Alexanderson, et al. ∙

research

∙ 12/10/2020

Full-Glow: Fully conditional Glow for more realistic image generation

Autonomous agents, such as driverless cars, require large amounts of lab...

0 Moein Sorkhei, et al. ∙

research

∙ 07/16/2020

Moving fast and slow: Analysis of representations and post-processing in speech-driven automatic gesture generation

This paper presents a novel framework for speech-driven gesture producti...

0 Taras Kucherenko, et al. ∙

research

∙ 06/11/2020

Robust model training and generalisation with Studentising flows

Normalising flows are tractable probabilistic models that leverage the p...

0 Simon Alexanderson, et al. ∙

research

∙ 06/11/2020

Let's face it: Probabilistic multi-modal interlocutor-aware generation of facial gestures in dyadic settings

To enable more natural face-to-face interactions, conversational agents ...

0 Patrik Jonell, et al. ∙

research

∙ 01/25/2020

Gesticulator: A framework for semantically-aware speech-driven gesture generation

During speech, people spontaneously gesticulate, which plays a key role ...

0 Taras Kucherenko, et al. ∙

research

∙ 11/10/2019

Transformation of low-quality device-recorded speech to high-quality speech using improved SEGAN model

Nowadays vast amounts of speech data are recorded from low-quality recor...

0 Seyyed Saeed Sarfjoo, et al. ∙

research

∙ 05/16/2019

MoGlow: Probabilistic and controllable motion synthesis using normalising flows

Data-driven modelling and synthesis of motion data is an active research...

0 Gustav Eje Henter, et al. ∙

research

∙ 03/08/2019

Analyzing Input and Output Representations for Speech-Driven Gesture Generation

This paper presents a novel framework for automatic speech-driven gestur...

0 Taras Kucherenko, et al. ∙

research

∙ 07/30/2018

Deep Encoder-Decoder Models for Unsupervised Learning of Controllable Speech Synthesis

Generating versatile and appropriate synthetic speech requires control o...

0 Gustav Eje Henter, et al. ∙

research

∙ 07/30/2018

Kernel Density Estimation-Based Markov Models with Hidden State

We consider Markov models of stochastic processes where the next-step co...

0 Gustav Eje Henter, et al. ∙

research

∙ 07/28/2018

Analysing Shortcomings of Statistical Parametric Speech Synthesis

Output from statistical parametric speech synthesis (SPSS) remains notic...

0 Gustav Eje Henter, et al. ∙

research

∙ 12/27/2017

Consensus-based Sequence Training for Video Captioning

Captioning models are typically trained using the cross-entropy loss. Ho...

0 Sang Phan, et al. ∙

research

∙ 08/22/2016

Median-Based Generation of Synthetic Speech Durations using a Non-Parametric Approach

This paper proposes a new approach to duration modelling for statistical...

0 Srikanth Ronanki, et al. ∙

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