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Text-To-Speech Synthesis

Text-To-Speech Synthesis is a machine learning task that involves converting written text into spoken words. The goal is to generate synthetic speech that sounds natural and resembles human speech as closely as possible.

Papers

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Showing 51–100 of 332 papers

TitleStatusHype
Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale CorpusCode1
Multilingual Text-to-Speech Synthesis for Turkic Languages Using TransliterationCode1
MnTTS2: An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis DatasetCode1
MnTTS: An Open-Source Mongolian Text-to-Speech Synthesis Dataset and Accompanied BaselineCode1
EdiTTS: Score-based Editing for Controllable Text-to-SpeechCode1
ArTST: Arabic Text and Speech TransformerCode1
QS-TTS: Towards Semi-Supervised Text-to-Speech Synthesis via Vector-Quantized Self-Supervised Speech Representation LearningCode1
UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal PromptsCode1
Enhancing Speech Intelligibility in Text-To-Speech Synthesis using Speaking Style ConversionCode1
Learning Arousal-Valence Representation from Categorical Emotion Labels of SpeechCode1
KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis DatasetCode1
Unsupervised Text-to-Speech Synthesis by Unsupervised Automatic Speech RecognitionCode1
Wave-Tacotron: Spectrogram-free end-to-end text-to-speech synthesisCode1
Textless Unit-to-Unit training for Many-to-Many Multilingual Speech-to-Speech TranslationCode1
Grad-TTS: A Diffusion Probabilistic Model for Text-to-SpeechCode1
Imaginary Voice: Face-styled Diffusion Model for Text-to-SpeechCode1
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyoneCode1
Automatic Prosody Annotation with Pre-Trained Text-Speech ModelCode1
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech SynthesisCode1
Fine-grained style control in Transformer-based Text-to-speech SynthesisCode1
FastSpeech 2: Fast and High-Quality End-to-End Text to SpeechCode1
Exploring Transfer Learning for Low Resource Emotional TTSCode1
In Other News: A Bi-style Text-to-speech Model for Synthesizing Newscaster Voice with Limited DataCode1
Improved Child Text-to-Speech Synthesis through Fastpitch-based Transfer LearningCode1
Accented Text-to-Speech Synthesis with a Conditional Variational AutoencoderCode1
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment SearchCode1
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech SynthesisCode0
Tools and resources for Romanian text-to-speech and speech-to-text applicationsCode0
Towards Lifelong Learning of Multilingual Text-To-Speech SynthesisCode0
Voicebox: Text-Guided Multilingual Universal Speech Generation at ScaleCode0
Systematic Inequalities in Language Technology Performance across the World’s LanguagesCode0
Systematic Inequalities in Language Technology Performance across the World's LanguagesCode0
Comparison of Speech Representations for Automatic Quality Estimation in Multi-Speaker Text-to-Speech SynthesisCode0
The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation SystemsCode0
Spoofing Speaker Verification Systems with Deep Multi-speaker Text-to-speech SynthesisCode0
Speech Synthesis from Text and Ultrasound Tongue Image-based Articulatory InputCode0
Attentive Multi-Layer Perceptron for Non-autoregressive GenerationCode0
Preparing an Endangered Language for the Digital Age: The Case of Judeo-SpanishCode0
Non-Autoregressive Neural Text-to-SpeechCode0
Multimodal Latent Language Modeling with Next-Token DiffusionCode0
Bayesian Parameter-Efficient Fine-Tuning for Overcoming Catastrophic ForgettingCode0
MIA-Prognosis: A Deep Learning Framework to Predict Therapy ResponseCode0
Effective parameter estimation methods for an ExcitNet model in generative text-to-speech systemsCode0
Mlphon: A Multifunctional Grapheme-Phoneme Conversion Tool Using Finite State TransducersCode0
ECAPA-TDNN for Multi-speaker Text-to-speech SynthesisCode0
Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition ErrorsCode0
MelNet: A Generative Model for Audio in the Frequency DomainCode0
Phrase break prediction with bidirectional encoder representations in Japanese text-to-speech synthesisCode0
Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent languageCode0
Direct speech-to-speech translation with a sequence-to-sequence modelCode0
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All datasetsLJSpeech20000 utterancesCMUDict 0.7bHUI speech corpusThorsten voice 21.02 neutralTrinity Speech-Gesture Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NaturalSpeechAudio Quality MOS4.56—Unverified
2VITSAudio Quality MOS4.43—Unverified
3Grad-TTS + HiFiGAN (1000 steps)Audio Quality MOS4.37—Unverified
4FastSpeech 2 + HiFiGANAudio Quality MOS4.34—Unverified
5Glow-TTS + HiFiGANAudio Quality MOS4.34—Unverified
6FastSpeech 2 + HiFiGANAudio Quality MOS4.32—Unverified
7FastDiff (4 steps)Audio Quality MOS4.28—Unverified
8FastDiff-TTSAudio Quality MOS4.03—Unverified
9Transformer TTS (Mel + WaveGlow)Audio Quality MOS3.88—Unverified
10FastSpeech (Mel + WaveGlow)Audio Quality MOS3.84—Unverified
#ModelMetricClaimedVerifiedStatus
1Mia10-keyword Speech Commands dataset16—Unverified
#ModelMetricClaimedVerifiedStatus
1Token-Level Ensemble DistillationPhoneme Error Rate4.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score3.74—Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score3.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Match-TTSGMOS3.7—Unverified