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Description

Canopy Labs has unveiled Orpheus, an innovative suite of advanced speech large language models (LLMs) aimed at achieving human-like speech generation capabilities. Utilizing the Llama-3 architecture, these models have been trained on an extensive dataset comprising over 100,000 hours of English speech, allowing them to generate speech that exhibits natural intonation, emotional depth, and rhythmic flow that outperforms existing high-end closed-source alternatives. Orpheus also features zero-shot voice cloning, enabling users to mimic voices without any need for prior fine-tuning, and provides easy-to-use tags for controlling emotion and intonation. The models are engineered for low latency, achieving approximately 200ms streaming latency for real-time usage, which can be further decreased to around 100ms when utilizing input streaming. Canopy Labs has made available both pre-trained and fine-tuned models with 3 billion parameters under the flexible Apache 2.0 license, with future intentions to offer smaller models with 1 billion, 400 million, and 150 million parameters to cater to devices with limited resources. This strategic move is expected to broaden accessibility and application potential across various platforms and use cases.

Description

Zyphra is thrilled to unveil the beta release of Zonos-v0.1, which boasts two sophisticated and real-time text-to-speech models that include high-fidelity voice cloning capabilities. Our release features both a 1.6B transformer and a 1.6B hybrid model, all under the Apache 2.0 license. Given the challenges in quantitatively assessing audio quality, we believe that the generation quality produced by Zonos is on par with or even surpasses that of top proprietary TTS models currently available. Additionally, we are confident that making models of this quality publicly accessible will greatly propel advancements in TTS research. You can find the Zonos model weights on Huggingface, with sample inference code available on our GitHub repository. Furthermore, Zonos can be utilized via our model playground and API, which offers straightforward and competitive flat-rate pricing options. To illustrate the performance of Zonos, we have prepared a variety of sample comparisons between Zonos and existing proprietary models, highlighting its capabilities. This initiative emphasizes our commitment to fostering innovation in the field of text-to-speech technology.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

GitHub Yes 
Hugging Face Yes 
Baseten Yes 
Google Colab Yes 
Llama 3 Yes 
VoiSpark Yes 

Integrations

GitHub Yes 
Hugging Face Yes 
Baseten No 
Google Colab No 
Llama 3 No 
VoiSpark No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

$0.02 per minute
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Canopy Labs

Country

United States

Website

canopylabs.ai/model-releases

Vendor Details

Company Name

Zyphra

Country

United States

Website

www.zyphra.com/post/beta-release-of-zonos-v0-1

Product Features

Text to Speech

API No 
Adjust Speaking Rate / Pitch No 
Audio Optimization No 
Custom Lexicons No 
Different Voice Choices No 
Multi-Language Support No 
Synchronize Speech No 

Product Features

Text to Speech

API No 
Adjust Speaking Rate / Pitch No 
Audio Optimization No 
Custom Lexicons No 
Different Voice Choices No 
Multi-Language Support No 
Synchronize Speech No 

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