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Sesame
Compared to Transkriptor
Sesame vs Transkriptor
Comparing the features of Sesame to Transkriptor
Feature
Sesame
Transkriptor
Capability Features
100+ Languages Supported
100
99% Accuracy
99%
AI Transcription
Audio and Video Input
Audio
Video
Call Transcription
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Instant Transcription
Interview Transcription
Meeting Transcription
Model Sizes
Tiny: 1B backbone, 100M decoder
Small: 3B backbone, 250M decoder
Medium: 8B backbone, 300M decoder
Multiple Speaker Handling
Objective Metrics
Word Error Rate
Speaker Similarity
Homograph Disambiguation
Pronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Pronunciation Correction
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
Text
Audio
Training Epochs
5
Integration Features
GitHub Release
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer
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
Free Preview
Free Tier
Open Source
Apache 2.0