Expressive Speech Synthesis
10 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Expressive Speech Synthesis
Most implemented papers
Exploring Transfer Learning for Low Resource Emotional TTS
Emotional-Text-to-Speech/dl-for-emo-tts
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Advances in Intelligent Systems and Computing 2019
During the last few years, spoken language technologies have known a big improvement thanks to Deep Learning.
Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron
syang1993/gst-tacotron
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ICML 2018
We present an extension to the Tacotron speech synthesis architecture that learns a latent embedding space of prosody, derived from a reference acoustic representation containing the desired prosody.
Enhancing Suno's Bark Text-to-Speech Model: Addressing Limitations Through Meta's Encodec and Pre-Trained Hubert
serp-ai/bark-with-voice-clone
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Social Science Research Network (SSRN) 2023
Keywords: Bark, ai voice cloning, Suno, text-to-speech, artificial intelligence, audio generation, Meta's encodec, audio codebooks, semantic tokens, HuBert, transformer-based model, multilingual speech, wav2vec, linear projection head, embedding space, generative capabilities, pretrained model checkpoints
Robust and fine-grained prosody control of end-to-end speech synthesis
keonlee9420/Robust_Fine_Grained_Prosody_Control
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We propose prosody embeddings for emotional and expressive speech synthesis networks.
Visualization and Interpretation of Latent Spaces for Controlling Expressive Speech Synthesis through Audio Analysis
noetits/ICE-Talk
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The field of Text-to-Speech has experienced huge improvements last years benefiting from deep learning techniques.
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.
Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech
keonlee9420/Cross-Speaker-Emotion-Transfer
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In expressive speech synthesis, there are high requirements for emotion interpretation.
EMNS /Imz/ Corpus: An emotive single-speaker dataset for narrative storytelling in games, television and graphic novels
The increasing adoption of text-to-speech technologies has led to a growing demand for natural and emotive voices that adapt to a conversation's context and emotional tone.
SC VALL-E: Style-Controllable Zero-Shot Text to Speech Synthesizer
Expressive speech synthesis models are trained by adding corpora with diverse speakers, various emotions, and different speaking styles to the dataset, in order to control various characteristics of speech and generate the desired voice.
DiffProsody: Diffusion-based Latent Prosody Generation for Expressive Speech Synthesis with Prosody Conditional Adversarial Training
Expressive text-to-speech systems have undergone significant advancements owing to prosody modeling, but conventional methods can still be improved.
