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Made in Vancouver, Canada by Picovoice
Leopard is an on-device speech-to-text engine. Leopard is:
pip3 install pvleopard
Leopard requires a valid Picovoice AccessKey
at initialization. AccessKey
acts as your credentials when using Leopard SDKs.
You can get your AccessKey
for free. Make sure to keep your AccessKey
secret.
Signup or Login to Picovoice Console to get your AccessKey
.
Create an instance of the engine and transcribe an audio file:
import pvleopard
leopard = pvleopard.create(access_key='${ACCESS_KEY}')
transcript, words = leopard.process_file('${AUDIO_FILE_PATH}')
print(transcript)
for word in words:
print(
"{word=\"%s\" start_sec=%.2f end_sec=%.2f confidence=%.2f speaker_tag=%d}"
% (word.word, word.start_sec, word.end_sec, word.confidence, word.speaker_tag))
Replace ${ACCESS_KEY}
with yours obtained from Picovoice Console and
${AUDIO_FILE_PATH}
to the path an audio file.
Finally, when done be sure to explicitly release the resources:
leopard.delete()
The Leopard Python SDK comes preloaded with a default English language model (.pv
file).
Default models for other supported languages can be found in lib/common.
Create custom language models using the Picovoice Console. Here you can train language models with custom vocabulary and boost words in the existing vocabulary.
Pass in the .pv
file via the model_path
argument:
leopard = pvleopard.create(
access_key='${ACCESS_KEY}',
model_path='${MODEL_FILE_PATH}')
Along with the transcript, Leopard returns metadata for each transcribed word. Available metadata items are:
[0, 1]
.0
reserved for unknown speakers. If speaker diarization is not enabled, the value will always be -1
.pvleoparddemo provides command-line utilities for processing audio using Leopard.
FAQs
Leopard Speech-to-Text Engine.
We found that pvleopard demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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