Speechlab vs Sesame

Comparing the features of Speechlab to Sesame

Feature
Speechlab
Sesame

Capability Features

Advanced Audio Editor
Audio and Video Support
Bulk Uploads and Processing
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Customizable Output
Dataset Size
1 million hours
Designed for Live Events
Dubbing
Emotional Intelligence
Evaluation Suite
Granular Audio Adjustment
Human Quality Review
Invoice Billing
Language Pairs Supported
300
Languages Supported (Dubbing)
20
Languages Supported (Live)
60
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multiple Speaker Handling
Multiple Speakers Support
No Multiple AI Solutions Needed
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Project Collaboration
Pronunciation Correction
Real-time AI Interpretation
Role-Based Access Control
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Training Epochs
5
Transcription
Translation
Ultra Low Latency
Voice Cloning
Workflow Compatibility

Integration Features

API Integrations
Custom AV Integrations
File Format Flexibility
Any format
GitHub Release
Google Meet Integration
LLama Architecture Backbone
Media Asset System Integration
Microsoft Teams Integration
Mimi Split-RVQ Tokenizer
Translation Management Integration
Zoom Integration

Limitation Features

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

Pricing Features

Enterprise Features
Free Preview
Free Trial
Open Source
Apache 2.0