SOTAVerified

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

Showing 276300 of 332 papers

TitleStatusHype
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder0
The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation SystemsCode0
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech SynthesisCode0
Design and Development of Speech Corpora for Air Traffic Control Training0
Improving homograph disambiguation with supervised machine learning0
SynPaFlex-Corpus: An Expressive French Audiobooks Corpus dedicated to expressive speech synthesis.0
Speaker-independent raw waveform model for glottal excitation0
Machine Speech Chain with One-shot Speaker Adaptation0
Tools and resources for Romanian text-to-speech and speech-to-text applicationsCode0
Creating New Language and Voice Components for the Updated MaryTTS Text-to-Speech Synthesis Platform0
Refer-iTTS: A System for Referring in Spoken Installments to Objects in Real-World Images0
Listening while Speaking: Speech Chain by Deep Learning0
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface0
Automatic Syllabification for Manipuri language0
DNN-based Speech Synthesis for Indian Languages from ASCII text0
A Taxonomy of Specific Problem Classes in Text-to-Speech Synthesis: Comparing Commercial and Open Source Performance0
Minimally Supervised Number Normalization0
Text Normalization and Unit Selection for a Memory Based Non Uniform Unit Selection TTS in Malayalam0
Hierarchical Representation of Prosody for Statistical Speech Synthesis0
Which Synthetic Voice Should I Choose for an Evocative Task?0
Individuality-Preserving Spectrum Modification for Articulation Disorders Using Phone Selective Synthesis0
A distributed cloud-based dialog system for conversational application development0
Aligning Opinions: Cross-Lingual Opinion Mining with Dependencies0
An In-depth Analysis of the Effect of Text Normalization in Social Media0
Normalization of Non-Standard Words in Croatian Texts0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NaturalSpeechAudio Quality MOS4.56Unverified
2VITSAudio Quality MOS4.43Unverified
3Grad-TTS + HiFiGAN (1000 steps)Audio Quality MOS4.37Unverified
4FastSpeech 2 + HiFiGANAudio Quality MOS4.34Unverified
5Glow-TTS + HiFiGANAudio Quality MOS4.34Unverified
6FastSpeech 2 + HiFiGANAudio Quality MOS4.32Unverified
7FastDiff (4 steps)Audio Quality MOS4.28Unverified
8FastDiff-TTSAudio Quality MOS4.03Unverified
9Transformer TTS (Mel + WaveGlow)Audio Quality MOS3.88Unverified
10FastSpeech (Mel + WaveGlow)Audio Quality MOS3.84Unverified
#ModelMetricClaimedVerifiedStatus
1Mia10-keyword Speech Commands dataset16Unverified
#ModelMetricClaimedVerifiedStatus
1Token-Level Ensemble DistillationPhoneme Error Rate4.6Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score3.74Unverified
#ModelMetricClaimedVerifiedStatus
1Tacotron 2Mean Opinion Score3.49Unverified
#ModelMetricClaimedVerifiedStatus
1Match-TTSGMOS3.7Unverified