OpenAI Text To Speech vs Sesame

Comparing the features of OpenAI Text To Speech to Sesame

Feature
OpenAI Text To Speech
Sesame

Capability Features

Age Selection
Audio Settings
Audio Speed Setting Range
1
Bookmark Page
Consistent Personality
Context Awareness
Conversational Dynamics
Conversational Speech Generation
Country Selection
Create Speech Button
Custom Voice Selection
AlloyEchoFableOnyxNovaShimmerAshCoralSage
Dataset Size
1 million hours
Emotional Intelligence
Evaluation Suite
Favorite Voice Option
Gender Selection
High Quality Voices
Integrated Audio Player
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
Pronunciation Correction
Reset Filters
Sample Playback
Sequence Length
2048
Single-Stage Model
Subjective Metrics
Comparative Mean Opinion Score
Text and Audio Input
TextAudio
Text to Speech
Training Epochs
5
Voice Characteristics
NeutralProfessionalClearWarmFriendlyEngagingEnergeticExpressiveMatureExperiencedYoungOldFemaleMaleLivelyVibrantDynamicCheerfulCommunity-orientedWiseCalmKnowledgeable

Integration Features

API Integrations
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
Pricing Information
Processing Delay
Real-Time Generation Delay
RVQ time-to-first-audio scales poorly
Video Tutorial Requirement
Watch 30 seconds

Pricing Features

Free Preview
Open Source
Apache 2.0