ChatTTS vs Sesame

Comparing the features of ChatTTS to Sesame

Feature
ChatTTS
Sesame

Capability Features

Community Support
Consistent Personality
Context Awareness
Continuous Improvement
Controllability and Security
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Detailed Documentation
Dialog Task Optimization
Easy to Use
Emotional Intelligence
Evaluation Suite
Fine-tuning Supported
Full Model Training Hours
100000
High-Fidelity Speech Synthesis
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multilingual Support
ChineseEnglish
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Open Source
Apache 2.0
Open Source Model Training Hours
40000
Partial Multilingual Support Planned
Planned for 20+ languages
Pronunciation Correction
Sample Rate for Audio Output
24000
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Text to Speech
Training Epochs
5
Voice Customization Options

Integration Features

API Integrations
GitHub Release
Gradio Demo Integration
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer
Platform Compatibility
Web applicationsMobile appsDesktop softwareEmbedded systems
PyTorch Dependency
SDK Programming Language Support
Multiple programming languages

Limitation Features

Cannot Model Conversation Structure
English Language Dominance
Memory Bottleneck in Training
No Pre-trained Language Model Use
Not All Languages Supported
Real-Time Generation Delay
RVQ time-to-first-audio scales poorly
Requires Significant Compute
High computational resources needed
Speech Quality Depends on Input
Varies with text complexity and length

Pricing Features

Free Preview
Free Tier
No Explicit Paid Plans Shown