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Orca Streaming Text-to-Speech Engine Python Demo

Made in Vancouver, Canada by Picovoice

Orca

Orca is an on-device streaming text-to-speech engine that is designed for use with LLMs, enabling zero-latency voice assistants. Orca is:

  • Private; All speech synthesis runs locally.
  • Cross-Platform:
    • Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64, arm64)
    • Android and iOS
    • Chrome, Safari, Firefox, and Edge
    • Raspberry Pi (3, 4, 5)

Compatibility

  • Python 3.9+
  • Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64, arm64), and Raspberry Pi (3, 4, 5).

Installation

pip3 install pvorcademo

AccessKey

Orca requires a valid Picovoice AccessKey at initialization. AccessKey acts as your credentials when using Orca 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.

Usage

Orca supports two modes of operation: streaming and single synthesis.

In the streaming synthesis mode, Orca processes an incoming text stream in real-time and generates audio in parallel. This is demonstrated in the Orca streaming demo.

In the single synthesis mode, the text is synthesized in a single call to the Orca engine.

Streaming synthesis demo

In this demo, we simulate a response from a language model by creating a text stream from a user-defined text. We stream that text to Orca and play the synthesized audio as soon as it gets generated.

To run it, execute the following:

python3 orca_demo_streaming.py --access_key ${ACCESS_KEY} --model_path ${MODEL_PATH} --text_to_stream ${TEXT}

Replace ${ACCESS_KEY} with your AccessKey obtained from Picovoice Console, ${MODEL_PATH} with a path to any of the model files available under lib/common, and ${TEXT} with your text to be streamed to Orca. Please note that this demo was not tested on macOS.

Single synthesis demo

To synthesize speech in a single call to Orca and without audio playback, run the following:

python3 orca_demo.py --access_key ${ACCESS_KEY} --model_path ${MODEL_PATH} --text ${TEXT} --output_path ${WAV_OUTPUT_PATH}

Replace ${ACCESS_KEY} with yours obtained from Picovoice Console, ${MODEL_PATH} with a path to any of the model files available under lib/common, ${TEXT} with your text to be synthesized, and ${WAV_OUTPUT_PATH} with a path to a .wav file where the generated audio will be stored as a single-channel, 16-bit PCM .wav file.

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