Get accurate speech recognition with FireRedASR2, supporting multiple languages and dialects, for startup founders needing robust ASR solutions.
advancedโฑ 1-2 days๐ต Free + LLM API costs
591 stars41 forksPythonQuality 8/10Updated 6/2/2026100% free ยท open source
What it is
Use FireRedASR2 to recognize and understand speech from audio.
What you can make with it
Automations like creating smart transcripts of customer calls for your business and analyzing customer sentiment from those conversations.
How it helps
It helps you accurately process speech from various languages and dialects, making it suitable for global customer support and product reviews.
Real use case example
"A founder wants to analyze customer satisfaction from call center recordings. She uploads the audio to FireRedASR2 to generate transcripts. Then, she trains a machine learning model to find keywords expressing dissatisfaction. Within weeks, she identifies frequent pain points and adjusts her product features to match customer needs."
If you're new
Try this when you're new to speech recognition and want a robust solution that doesn't break the bank.
If you're senior
Reach for this when you need an industrial-grade ASR solution with multi-language support that's scalable and free.
Common confusion cleared up
Don't confuse FireRedASR2 with simpler, smaller-scale ASR services โ it's designed for demanding industrial applications.
Best inside these AI tools
Self-hosted
Pairs with
Stripe webhookNotion database
Why we list it on WorkflowStacks: It's here because it's an industrial-grade, free, and open-source ASR solution, saving you costs compared to similar commercial tools.
What it does
FireRedASR2S provides highly accurate speech recognition capabilities, supporting multiple languages and dialects, including Chinese, English, and code-switching between languages.
Install / run
git clone https://github.com/FireRedTeam/FireRedASR2S.git && cd FireRedASR2S
When to use it
โขWhen you need to transcribe speech or singing in various languages and dialects with high accuracy
โขWhen your application requires robust speech recognition for both speech and music
โขWhen you need to support a wide range of languages, including those with complex dialects and accents
Quick start
1Modify the `config.yaml` file to specify the language and dialect you want to use for speech recognition
2Run `python -m firered.asr.infer` to start the speech recognition inference process
3Use the `firered.asr` module in your Python script to integrate speech recognition capabilities into your application
4Refer to the `examples` directory for sample code and configuration files to get started quickly
5Check the `README.md` file for detailed documentation and instructions on how to use FireRedASR2S
Heads up: Make sure you have the required libraries and dependencies installed, including PyTorch and TensorFlow, and that your system meets the minimum requirements specified in the README.md file
Saves to your device
Topics
asr
asr-pipeline
audio-event-classification
audio-event-detection
automatic-speech-recognition
industrial-grade
language-identification
lid
llm
multimodal-llm
open-source
punctuation-prediction
punctuation-restoration
sota
speech-recognition
speechllm
vad
voice-activity-detection
What's inside โ free to inspect
No purchase needed
Read the entire source before you build โ unlike paid marketplaces that hide it behind a buy button.