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Found 10 papers, 1 papers with code
Evaluating Sampling-based Filler Insertion with Spontaneous TTS
Perceptual results show little difference between compared filler insertion models including with ground-truth, which may be due to the ambiguity of what is good filler insertion and a strong neural spontaneous TTS that produces natural speech irrespective of input.
On the Use of Self-Supervised Speech Representations in Spontaneous Speech Synthesis
Prior work has shown that SSL is an effective intermediate representation in two-stage text-to-speech (TTS) for both read and spontaneous speech.
Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis
With read-aloud speech synthesis achieving high naturalness scores, there is a growing research interest in synthesising spontaneous speech.
Automatic Evaluation of Turn-taking Cues in Conversational Speech Synthesis
Turn-taking is a fundamental aspect of human communication where speakers convey their intention to either hold, or yield, their turn through prosodic cues.
A Comparative Study of Self-Supervised Speech Representations in Read and Spontaneous TTS
Recent work has explored using self-supervised learning (SSL) speech representations such as wav2vec2. 0 as the representation medium in standard two-stage TTS, in place of conventionally used mel-spectrograms.
Integrated Speech and Gesture Synthesis
Text-to-speech and co-speech gesture synthesis have until now been treated as separate areas by two different research communities, and applications merely stack the two technologies using a simple system-level pipeline.
Theory of the Chromatic Dispersion, Revisited
We derive general analytic expressions for the chromatic dispersion orders valid to infinity, due to the k vector or phase {\phi} dependence on the wavelength.
Optics Applied Physics Atomic and Molecular Clusters
Unaligned Image-to-Sequence Transformation with Loop Consistency
We tackle the problem of modeling sequential visual phenomena.
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers
Video Captioning and Summarization have become very popular in the recent years due to advancements in Sequence Modelling, with the resurgence of Long-Short Term Memory networks (LSTMs) and introduction of Gated Recurrent Units (GRUs).
Controllable Top-down Feature Transformer
We study the intrinsic transformation of feature maps across convolutional network layers with explicit top-down control.
