mlsanityData to 7 Oct 2026

Emotional speech synthesis with rich and granularized control

arXiv 1911.01635 ↗First posted 5 Nov 2019eess.AS cs.SDcited by 28

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Abstract (arXiv)

This paper proposes an effective emotion control method for an end-to-end text-to-speech (TTS) system. To flexibly control the distinct characteristic of a target emotion category, it is essential to determine embedding vectors representing the TTS input. We introduce an inter-to-intra emotional distance ratio algorithm to the embedding vectors that can minimize the distance to the target emotion category while maximizing its distance to the other emotion categories. To further enhance the expressiveness of a target speech, we also introduce an effective interpolation technique that enables the intensity of a target emotion to be gradually changed to that of neutral speech. Subjective evaluation results in terms of emotional expressiveness and controllability show the superiority of the proposed algorithm to the conventional methods.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2019.

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Citing papers per year: 2021: 6; 2022: 6; 2023: 6; 2024: 7; 2025: 3.

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  1. 2021A Survey on Neural Speech Synthesiscited by 182
  2. 2023Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language Modelingcited by 166
  3. 2021Emotional Voice Conversion: Theory, Databases and ESDcited by 113
  4. 2022EmoDiff: Intensity Controllable Emotional Text-to-Speech with Soft-Label Guidancecited by 37
  5. 2022Emotion Intensity and its Control for Emotional Voice Conversioncited by 35
  6. 2022An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Eracited by 32
  7. 2022Speech Synthesis with Mixed Emotionscited by 28
  8. 2024Towards Controllable Speech Synthesis in the Era of Large Language Models: A Systematic Surveycited by 22
  9. 2021Reinforcement Learning for Emotional Text-to-Speech Synthesis with Improved Emotion Discriminabilitycited by 19
  10. 2023EmoMix: Emotion Mixing via Diffusion Models for Emotional Speech Synthesiscited by 19
  11. 2024EmoSphere++: Emotion-Controllable Zero-Shot Text-to-Speech via Emotion-Adaptive Spherical Vectorcited by 19
  12. 2023ZET-Speech: Zero-shot adaptive Emotion-controllable Text-to-Speech Synthesis with Diffusion and Style-based Modelscited by 14
16 more
  1. 2023EmoSpeech: Guiding FastSpeech2 Towards Emotional Text to Speechcited by 14
  2. 2024DurFlex-EVC: Duration-Flexible Emotional Voice Conversion Leveraging Discrete Representations without Text Alignmentcited by 8
  3. 2024A Review of Human Emotion Synthesis Based on Generative Technologycited by 7
  4. 2021Review of end-to-end speech synthesis technology based on deep learningcited by 6
  5. 2021Facetron: A Multi-speaker Face-to-Speech Model based on Cross-modal Latent Representationscited by 4
  6. 2024Exploring speech style spaces with language models: Emotional TTS without emotion labelscited by 4
  7. 2025Prompt-Unseen-Emotion: Zero-shot Expressive Speech Synthesis with Prompt-LLM Contextual Knowledge for Mixed Emotionscited by 4
  8. 2022Emotion Selectable End-to-End Text-based Speech Editingcited by 3
  9. 2022Semi-supervised learning for continuous emotional intensity controllable speech synthesis with disentangled representationscited by 2
  10. 2024EmoReg: Directional Latent Vector Modeling for Emotional Intensity Regularization in Diffusion-based Voice Conversioncited by 2
  11. 2021Multi-speaker Emotional Text-to-speech Synthesizercited by 1
  12. 2023Expressive TTS Driven by Natural Language Prompts Using Few Human Annotationscited by 1
  13. 2024EmoSpeech: A Corpus of Emotionally Rich and Contextually Detailed Speech Annotationscited by 1
  14. 2025MultiGen: Child-Friendly Multilingual Speech Generator with LLMscited by 1
  15. 2025RLAIF-SPA: Structured AI Feedback for Semantic-Prosodic Alignment in Speech Synthesiscited by 1
  16. 2023CASEIN: Cascading Explicit and Implicit Control for Fine-grained Emotion Intensity Regulationcited by 0