Sesame vs Voxabot

Comparing the features of Sesame to Voxabot

Feature
Sesame
Voxabot

Capability Features

Automatic Engine Updates
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Export SSML
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Pronunciation Correction
Sequence Length
2048
Single-Stage Model
SSML Editor
SSML Support
Subjective Metrics
Comparative Mean Opinion Score
Supported Language List
150
Supported Voices
820
Text and Audio Input
TextAudio
Training Epochs
5
Unified API Login
User Data Privacy
Visual Edit Preview
Waveform Visualization

Integration Features

GitHub Release
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer
SSML Download Format
text file
Text to Speech
GoogleAzureAWS

Limitation Features

Cannot Model Conversation Structure
English Language Dominance
Memory Bottleneck in Training
No Microsoft Azure Subscription Required
No Pre-trained Language Model Use
Real-Time Generation Delay
RVQ time-to-first-audio scales poorly

Pricing Features

Free Preview
Free Tier
Neural TTS Pricing Parity
No Royalties
Open Source
Apache 2.0
Pricing Plan Details