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FireRedASR

An open source industrial-grade Mandarin automatic speech recognition model that supports a variety of application scenarios.

#Artificial Intelligence
#Open source
#Multi-language support
#speech recognition
#Industrial grade applications
FireRedASR

Product Details

FireRedASR is an open source industrial-grade Mandarin automatic speech recognition model that uses Encoder-Decoder and LLM integrated architecture. It comes in two variants: FireRedASR-LLM and FireRedASR-AED, designed for high performance and energy efficiency requirements respectively. The model performed well on the Mandarin benchmark, as well as on dialect and English speech recognition. It is suitable for industrial-level applications that require efficient speech-to-text conversion, such as smart assistants, video subtitle generation, etc. The model is open source, making it easy for developers to integrate and optimize.

Main Features

1
Using the Encoder-Adapter-LLM framework to achieve end-to-end voice interaction
2
Supports multi-source Mandarin scenarios, such as videos, live broadcasts and smart assistants
3
Achieving low character error rate (CER) on Mandarin benchmark
4
Provides a compact model architecture suitable for resource-constrained applications
5
Supports dialect and English speech recognition to expand application scenarios
6
Open source model and inference code for easy integration and optimization by developers
7
Excellent performance in singing lyrics recognition, suitable for music-related applications

How to Use

1
Visit the project homepage to download open source code and model files
2
Choose FireRedASR-LLM or FireRedASR-AED model based on your needs
3
Use the provided inference code for speech recognition testing
4
Integrate models into applications for speech-to-text functionality
5
Adjust model parameters according to actual application scenarios to optimize performance

Target Users

This product is suitable for enterprises and developers who need efficient speech-to-text, especially those who need it in the fields of smart assistants, video subtitle generation, voice interaction applications, etc. The open source feature also makes it suitable for technical teams who want to carry out customized development.

Examples

Implement voice command recognition and interaction in smart voice assistants

Automatically generate accurate subtitle content for video platforms

Speech-to-text in Mandarin and dialects in a multilingual environment

Quick Access

Visit Website →

Categories

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› Development and Tools
› speech recognition

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