TranscribeAI vs Sesame

Comparing the features of TranscribeAI to Sesame

Feature
TranscribeAI
Sesame

Capability Features

Audio File Transcription
Conference Calls Analysis
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Domain-Specific Recognition
Emotional Intelligence
Evaluation Suite
Legal Transcription
Medical Data Transcription
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
MP3 to Text
Multiple Speaker Handling
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Podcast Transcription
Pronunciation Correction
Sequence Length
2048
Single-Stage Model
Speech to Text
Subjective Metrics
Comparative Mean Opinion Score
Subtitle Generation
Text and Audio Input
TextAudio
Training Epochs
5
Transcribe Interviews
Video to Text
Video Transcription
Voice Recognition

Integration Features

File Formats Supported
MP3Video
GitHub Release
Integrations Information
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
Pricing Plan Details
Not specified