HyperCatcher vs Sesame

Comparing the features of HyperCatcher to Sesame

Feature
HyperCatcher
Sesame

Capability Features

AI Powered Transcripts
Audio Transcription
Consistent Personality
Context Actions
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Export Transcripts
Instant Source Links
Local ML Transcription
Model Sizes
Tiny: 1B backbone, 100M decoderSmall: 3B backbone, 250M decoderMedium: 8B backbone, 300M decoder
Multiple Speaker Handling
Note Taking with Context
Objective Metrics
Word Error RateSpeaker SimilarityHomograph DisambiguationPronunciation Consistency
Partial Multilingual Support Planned
Planned for 20+ languages
Podcast Topic Suggestions
Pronunciation Correction
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Training Epochs
5

Integration Features

API or Plugin Integration
Audio and Video Support
File Formats Supported
GitHub Release
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer
Podcast Platform 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

Free Preview
Free Tier
Open Source
Apache 2.0