Software Tech

Live Audio Transcription with Python For Free

Unlike cloud speech-to-text APIs, Cheetah Streaming Speech-to-Text processes speech data locally on-device. Thus, it has a default advantage over

Live Audio Transcription with Python For Free

Unlike cloud -to-text APIs, Cheetah Streaming Speech-to-Text processes speech locally -device. Thus, it has default advantage over speech-to-text APIs when it comes to speed. No cloud speech-to-text can eliminate the network latency. They can be fast, but to a certain degree.

Let' learn to convert live audio to text using Picovoice Cheetah Streaming Speech-to-Text Python SDK, so can see it yourself.

1. Install Cheetah Streaming Speech-to-Text Python SDK

pip install pvcheetah

2. your AccessKey **Picovoice Console**
If you do not have an existing Picovoice Console Account, create one in minutes. No is required. You can enjoy the Forever-Free Plan, as the name suggests, forever!

3. Import Cheetah Streaming Speech-to-Text package:

import pvcheetah

4. Create an instance of the speech-to-text with your AccessKey:

handle = pvcheetah.create(access_key)

Don't forget to replace the placeholder with your AccessKey

5. Implement audio recording.
Cheetah Streaming Speech-to-Text processes audio whether it comes from a or another program.

For the following, we assume there is a function available to us that provides the next available audio chunk (frame) as below.

def get_next_audio_frame():

Convert live audio to text:

while True:
partial_transcript, is_endpoint = handle.process(get_next_audio_frame())
if is_endpoint:
final_transcript = handle.flush()

That' it! In 5 simple steps, you can get live audio converted into text!

For more , you can check

the original article,
how to evaluate live audio transcription engines
on-prem deployment options
the comparison of popular speech-to-text engines
advantages of local speech-to-text

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Dilek Karasoy

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