mlsanityData to 14 Oct 2026

EE-TTS: Emphatic Expressive TTS with Linguistic Information

arXiv 2305.12107 ↗First posted 20 May 2023cs.SD cs.CL eess.AScited by 4

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Abstract (arXiv)

While Current TTS systems perform well in synthesizing high-quality speech, producing highly expressive speech remains a challenge. Emphasis, as a critical factor in determining the expressiveness of speech, has attracted more attention nowadays. Previous works usually enhance the emphasis by adding intermediate features, but they can not guarantee the overall expressiveness of the speech. To resolve this matter, we propose Emphatic Expressive TTS (EE-TTS), which leverages multi-level linguistic information from syntax and semantics. EE-TTS contains an emphasis predictor that can identify appropriate emphasis positions from text and a conditioned acoustic model to synthesize expressive speech with emphasis and linguistic information. Experimental results indicate that EE-TTS outperforms baseline with MOS improvements of 0.49 and 0.67 in expressiveness and naturalness. EE-TTS also shows strong generalization across different datasets according to AB test results.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 21 of its 34 references that are in the map. First posted on arXiv 20 May 2023.

Builds on

21 of 34 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,863
  3. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,850
  4. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,154
  5. 2015Gated Graph Sequence Neural Networkscited by 796
  6. 2020FastSpeech 2: Fast and High-Quality End-to-End Text to Speechcited by 717
  7. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 561
  8. 2017Tacotron: Towards End-to-End Speech Synthesiscited by 490
  9. 2021A Survey on Neural Speech Synthesiscited by 184
  10. 2022NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Qualitycited by 152
  11. 2021AdaSpeech: Adaptive Text to Speech for Custom Voicecited by 98
  12. 2018Sample Efficient Adaptive Text-to-Speechcited by 45
9 more
  1. 2020Improving Prosody Modelling with Cross-Utterance BERT Embeddings for End-to-end Speech Synthesiscited by 27
  2. 2020DenoiSpeech: Denoising Text to Speech with Frame-Level Noise Modelingcited by 14
  3. 2021Speech BERT Embedding For Improving Prosody in Neural TTScited by 11
  4. 2022Self-supervised Context-aware Style Representation for Expressive Speech Synthesiscited by 10
  5. 2022BERT, can HE predict contrastive focus? Predicting and controlling prominence in neural TTS using a language modelcited by 10
  6. 2021Emphasis control for parallel neural TTScited by 9
  7. 2022Language Model-Based Emotion Prediction Methods for Emotional Speech Synthesis Systemscited by 9
  8. 2021Supervised and Unsupervised Approaches for Controlling Narrow Lexical Focus in Sequence-to-Sequence Speech Synthesiscited by 8
  9. 2021Improving Prosody for Unseen Texts in Speech Synthesis by Utilizing Linguistic Information and Noisy Datacited by 2

Built on by

Cited by year

Citing papers per year: 2024: 3; 2025: 1.

4 papers.

  1. 2024Emphasis Rendering for Conversational Text-to-Speech with Multi-modal Multi-scale Context Modelingcited by 6
  2. 2025Improving French Synthetic Speech Quality via SSML Prosody Controlcited by 1
  3. 2024GTR-Voice: Articulatory Phonetics Informed Controllable Expressive Speech Synthesiscited by 0
  4. 2024Word-wise intonation model for cross-language TTS systemscited by 0