SpeechGPT 2.0-preview
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Speechgpt 2.0 Preview
Overview :
SpeechGPT 2.0-preview is an advanced voice interaction model developed by the Natural Language Processing Laboratory at Fudan University. It employs vast amounts of voice data for training, achieving low-latency and highly natural speech interaction capabilities. The model simulates various emotional, stylistic, and role-based voice expressions while supporting tool invocation, online search, and access to external knowledge bases. Key advantages include strong voice style generalization, multi-role simulation, and low-latency interaction experience. Currently, the model supports Chinese voice interaction, with plans to expand to more languages in the future.
Target Users :
This product is ideal for scenarios requiring highly natural speech interactions, such as intelligent customer service, voice assistants, educational software, etc. It offers users a more vivid and natural voice interaction experience, enhancing user satisfaction and interaction efficiency.
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Top Region: US(100.00%)
Website Views : 52.4K
Use Cases
In intelligent customer service, quickly answer user questions through voice interactions to enhance service efficiency.
In educational software, simulate different roles for language learning to increase engagement.
As a voice assistant, respond to user commands in real-time, providing information such as weather and news.
Features
Supports multi-emotional, multi-style, and multi-tone voice interactions, with intelligent switching.
Features powerful role-playing capabilities to simulate the voice and emotional state of different characters.
Supports tool invocation, online search, and access to external knowledge bases, enhancing interactive intelligence.
Offers low-latency interaction with a delay of less than 200 milliseconds, ensuring a smooth real-time experience.
Supports various voice skills, including poetry recitation, storytelling, and dialect conversations.
Achieves ultra-low bitrate streaming voice encoding and decoding through semantic-acoustic joint modeling.
Adopts a hybrid voice-text modeling architecture to balance voice and text processing capabilities.
Provides open-source inference code, model weights, and methodology descriptions for easy use by developers.
How to Use
Visit the [Demo Page](https://sp2.open-moss.com/) to experience the speech interaction features.
Check out the open-source code and model weights on GitHub to learn about the technical details.
Select the appropriate speech interaction mode based on your needs, such as multi-emotion and multi-style.
Interact with the model in real-time through voice input to experience low-latency responses.
Utilize the model's tool invocation and search capabilities to obtain richer interaction content.
Perform secondary development or integration based on actual application scenarios in conjunction with the model's capabilities.
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