Sesame vs Wordcab

Comparing the features of Sesame to Wordcab

Feature
Sesame
Wordcab

Capability Features

Commercial APIs
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Human-Centric Voice AI
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
PII/PHI/PCI Detection
Proactive Email Assistant
Pronunciation Correction
Push-to-Talk Gateway
Sequence Length
2048
Single-Stage Model
Speechcatcher ASR Models
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Third-Party Collaboration
Training Epochs
5
Try Now Availability
Speechcatchertts-arena.comGLiNER-PII
TTS Model Benchmarking

Integration Features

GitHub Release
LLama Architecture Backbone
Mimi Split-RVQ Tokenizer
Platform Integrations
Desktop-native applications

Limitation Features

Cannot Model Conversation Structure
Coming Soon Products
ftt.devverbatim.so
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