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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 251–300 of 332 papers

TitleStatusHype
A unified sequence-to-sequence front-end model for Mandarin text-to-speech synthesis—0
Incremental Text-to-Speech Synthesis with Prefix-to-Prefix Framework—0
Spoofing Speaker Verification Systems with Deep Multi-speaker Text-to-speech SynthesisCode0
Effect of choice of probability distribution, randomness, and search methods for alignment modeling in sequence-to-sequence text-to-speech synthesis using hard alignment—0
The Theory behind Controllable Expressive Speech Synthesis: a Cross-disciplinary Approach—0
Modular Meta-Learning with Shrinkage—0
Evaluating Long-form Text-to-Speech: Comparing the Ratings of Sentences and Paragraphs—0
Neural Harmonic-plus-Noise Waveform Model with Trainable Maximum Voice Frequency for Text-to-Speech Synthesis—0
MelNet: A Generative Model for Audio in the Frequency DomainCode0
Listening while Speaking and Visualizing: Improving ASR through Multimodal Chain—0
Neural Text Normalization with Subword Units—0
Neural Models of Text Normalization for Speech Applications—0
Non-Autoregressive Neural Text-to-SpeechCode0
Effective parameter estimation methods for an ExcitNet model in generative text-to-speech systemsCode0
Direct speech-to-speech translation with a sequence-to-sequence modelCode0
Token-Level Ensemble Distillation for Grapheme-to-Phoneme Conversion—0
Speech denoising by parametric resynthesis—0
Generative adversarial network-based glottal waveform model for statistical parametric speech synthesis—0
AttS2S-VC: Sequence-to-Sequence Voice Conversion with Attention and Context Preservation Mechanisms—0
End-to-End Feedback Loss in Speech Chain Framework via Straight-Through Estimator—0
Waveform generation for text-to-speech synthesis using pitch-synchronous multi-scale generative adversarial networks—0
Speaking style adaptation in Text-To-Speech synthesis using Sequence-to-sequence models with attention—0
Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent languageCode0
A Challenge Set and Methods for Noun-Verb Ambiguity—0
Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis—0
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder—0
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 Training—0
Improving homograph disambiguation with supervised machine learning—0
SynPaFlex-Corpus: An Expressive French Audiobooks Corpus dedicated to expressive speech synthesis.—0
Speaker-independent raw waveform model for glottal excitation—0
Machine Speech Chain with One-shot Speaker Adaptation—0
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 Platform—0
Refer-iTTS: A System for Referring in Spoken Installments to Objects in Real-World Images—0
Listening while Speaking: Speech Chain by Deep Learning—0
CASSANDRA: A multipurpose configurable voice-enabled human-computer-interface—0
Automatic Syllabification for Manipuri language—0
DNN-based Speech Synthesis for Indian Languages from ASCII text—0
A Taxonomy of Specific Problem Classes in Text-to-Speech Synthesis: Comparing Commercial and Open Source Performance—0
Minimally Supervised Number Normalization—0
Text Normalization and Unit Selection for a Memory Based Non Uniform Unit Selection TTS in Malayalam—0
Hierarchical Representation of Prosody for Statistical Speech Synthesis—0
Which Synthetic Voice Should I Choose for an Evocative Task?—0
Individuality-Preserving Spectrum Modification for Articulation Disorders Using Phone Selective Synthesis—0
A distributed cloud-based dialog system for conversational application development—0
Aligning Opinions: Cross-Lingual Opinion Mining with Dependencies—0
An In-depth Analysis of the Effect of Text Normalization in Social Media—0
Normalization of Non-Standard Words in Croatian Texts—0
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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