Amazon Transcribe, Google Speech-to-Text, Azure Cognitive Services, IBM Watson, AssemblyAI, DeepGram, Speechmatics, and Rev, β¦all provide APIs to transcribe audio files. So why should you care about Picovoice Leopard? Just for the Free Tier? Nope! We have more reasons:
- Private: Voice data is processed on-device
- Accurate: Backed by an Open-Source Benchmark
- Compact and Computationally Efficient
- Cross-Platform: Runs on Linux, macOS, Windows, Android, iOS, Raspberry Pi, and NVIDIA Jetson
- Hyper-customizable: Self-service UI to customize models
- You can get started with 3 lines of code!
Let's get started!
1- Install
Install Leopard from a terminal:
pip3 install pvleoparddemo
2- Try it
Grab your free AccessKey from Picovoice Console and run the microphone demo from the terminal:
leopard_demo_mic --access_key ${YOUR_ACCESS_KEY}
3- Build
Create an instance of Leopard:
from pvleopard import *
o = create(access_key=${YOUR_ACCESS_KEY})
Transcribe an audio file:
transcript, words = o.process_file(${YOUR_AUDIO_FILE_PATH})
print(transcript)
Enjoy!
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