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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 1–25 of 332 papers

TitleStatusHype
Neural Codec Language Models are Zero-Shot Text to Speech SynthesizersCode7
ERNIE-SAT: Speech and Text Joint Pretraining for Cross-Lingual Multi-Speaker Text-to-SpeechCode6
PaddleSpeech: An Easy-to-Use All-in-One Speech ToolkitCode6
StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task LearningCode5
Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language ModelingCode5
ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow MatchingCode4
Enhancing Suno's Bark Text-to-Speech Model: Addressing Limitations Through Meta's Encodec and Pre-Trained HubertCode4
MoonCast: High-Quality Zero-Shot Podcast GenerationCode3
Matcha-TTS: A fast TTS architecture with conditional flow matchingCode3
ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-SpeechCode3
Lina-Speech: Gated Linear Attention is a Fast and Parameter-Efficient Learner for text-to-speech synthesisCode2
SSR-Speech: Towards Stable, Safe and Robust Zero-shot Text-based Speech Editing and SynthesisCode2
Sample-Efficient Diffusion for Text-To-Speech SynthesisCode2
EmoSphere-TTS: Emotional Style and Intensity Modeling via Spherical Emotion Vector for Controllable Emotional Text-to-SpeechCode2
CM-TTS: Enhancing Real Time Text-to-Speech Synthesis Efficiency through Weighted Samplers and Consistency ModelsCode2
Generative Adversarial Training for Text-to-Speech Synthesis Based on Raw Phonetic Input and Explicit Prosody ModellingCode2
LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPTCode2
FunCodec: A Fundamental, Reproducible and Integrable Open-source Toolkit for Neural Speech CodecCode2
A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous SpeechCode2
Towards Building Text-To-Speech Systems for the Next Billion UsersCode2
StyleTTS: A Style-Based Generative Model for Natural and Diverse Text-to-Speech SynthesisCode2
GenerSpeech: Towards Style Transfer for Generalizable Out-Of-Domain Text-to-SpeechCode2
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level QualityCode2
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech SynthesisCode2
iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier TransformCode2
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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