Home
Articles
Home
SpeechFlow
Compared to Sesame
SpeechFlow vs Sesame
Comparing the features of SpeechFlow to Sesame
Feature
SpeechFlow
Sesame
Capability Features
API Access
Audio to Text
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
High Accuracy Model
Top accuracy
Model Sizes
Tiny: 1B backbone, 100M decoder
Small: 3B backbone, 250M decoder
Medium: 8B backbone, 300M decoder
Multilingual Support
14
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
Speech to Text
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
Open Source
Apache 2.0