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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 26–50 of 332 papers

TitleStatusHype
Sample-Efficient Diffusion for Text-To-Speech SynthesisCode2
SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and SynthesisCode2
PortaSpeech: Portable and High-Quality Generative Text-to-SpeechCode2
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level QualityCode2
CM-TTS: Enhancing Real Time Text-to-Speech Synthesis Efficiency through Weighted Samplers and Consistency ModelsCode2
DiffSinger: Singing Voice Synthesis via Shallow Diffusion MechanismCode2
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech SynthesisCode2
Generative Adversarial Training for Text-to-Speech Synthesis Based on Raw Phonetic Input and Explicit Prosody ModellingCode2
Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale CorpusCode1
Multilingual Text-to-Speech Synthesis for Turkic Languages Using TransliterationCode1
MnTTS: An Open-Source Mongolian Text-to-Speech Synthesis Dataset and Accompanied BaselineCode1
MnTTS2: An Open-Source Multi-Speaker Mongolian Text-to-Speech Synthesis DatasetCode1
Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language ModelsCode1
Textless Unit-to-Unit training for Many-to-Many Multilingual Speech-to-Speech TranslationCode1
Learning Arousal-Valence Representation from Categorical Emotion Labels of SpeechCode1
KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis DatasetCode1
KazEmoTTS: A Dataset for Kazakh Emotional Text-to-Speech SynthesisCode1
UMETTS: A Unified Framework for Emotional Text-to-Speech Synthesis with Multimodal PromptsCode1
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment SearchCode1
Grad-TTS: A Diffusion Probabilistic Model for Text-to-SpeechCode1
Imaginary Voice: Face-styled Diffusion Model for Text-to-SpeechCode1
Fine-grained style control in Transformer-based Text-to-speech SynthesisCode1
ArTST: Arabic Text and Speech TransformerCode1
FastSpeech 2: Fast and High-Quality End-to-End Text to SpeechCode1
Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech SynthesisCode1
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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