Welcome to the world of speech recognition with FunASR! FunASR is designed to bridge the gap between academic research and industrial applications, providing an easy way to train and fine-tune speech recognition models. This guide will walk you through the essentials of getting started, from installation to troubleshooting common issues.

Highlights of FunASR

• Robust features: Speech Recognition (ASR), Voice Activity Detection (VAD), Punctuation Restoration, and more.
• Access a wide array of pre-trained models via the ModelScope and Huggingface.
• Ease of use with convenient scripts and tutorials.
• Support for service deployment with detailed documentation.

Installation

Getting started with FunASR is straightforward. You can either install it using pip or clone the repository to install from the source code:

pip3 install -U funasr
# Or install from source code
git clone https://github.com/alibaba/FunASR.git
cd FunASR
pip3 install -e .

Optionally, install modelscope for pretrained models:

pip3 install -U modelscope

Quick Start

Now, let’s dive into using FunASR for your speech recognition tasks!

Speech Recognition

Imagine you’re a librarian trying to sort through hundreds of audio books. Instead of having to listen to the entire book to find a specific sentence, you can use FunASR as your trusty assistant that transcribes your audio files into text:

from funasr import AutoModel

# Load the model
model = AutoModel(model='paraformer-zh', model_revision='v2.0.4')

# Generate transcriptions
res = model.generate(input='exampleasr_example.wav', batch_size_s=300)

# Print results
print(res)

This way, you get to focus on the important details without getting lost in the audio chaos!

Voice Activity Detection

For this task, let’s use the same logic as ensuring a mouse finds the cheese in a maze. The mouse (our model) listens for activity (voice) and detects when it can safely be activated:

from funasr import AutoModel

model = AutoModel(model='fsmn-vad', model_revision='v2.0.4')
res = model.generate(input='exampleasr_example.wav')
print(res)

Punctuation Restoration

Imagine you’re translating a whispering conversation. How would you punctuate it to convey emotion? FunASR takes care of this for you:

from funasr import AutoModel

model = AutoModel(model='ct-punc', model_revision='v2.0.4')
res = model.generate(input='那今天的会就到这里吧 happy new year 明年见')
print(res)

Troubleshooting

If you encounter any issues, here are some troubleshooting tips:

• Ensure all dependencies are installed correctly.
• Verify that the audio file exists and the path is correct.
• If you face memory issues, consider reducing the batch size of your input.
• Read the documentation for detailed setup instructions which can be found in the GitHub repository.
• For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

By following the steps outlined above, you can effectively harness the power of FunASR for your speech recognition needs. As you progress, feel free to explore its myriad features to enhance your applications.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.