Metadata-Version: 2.1
Name: pveagledemo
Version: 0.2.0
Summary: Eagle Speaker Recognition Engine demos
Home-page: https://github.com/Picovoice/eagle
Author: Picovoice
Author-email: hello@picovoice.ai
License: UNKNOWN
Description: # Eagle Speaker Recognition Demos
        
        Made in Vancouver, Canada by [Picovoice](https://picovoice.ai)
        
        ## Eagle
        
        Eagle is an on-device speaker recognition engine. Eagle is:
        
        - Private; All voice processing runs locally.
        - Cross-Platform:
            - Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64)
            - Android and iOS
            - Chrome, Safari, Firefox, and Edge
            - Raspberry Pi (4, 3) and NVIDIA Jetson Nano
        
        ## Compatibility
        
        - Python 3.5+
        - Runs on Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64), Raspberry Pi (4, 3), and NVIDIA Jetson Nano.
        
        ## Installation
        
        ```console
        pip3 install pveagledemo
        ```
        
        ## AccessKey
        
        Eagle requires a valid Picovoice `AccessKey` at initialization. `AccessKey` acts as your credentials when using Eagle
        SDKs. You can get your `AccessKey` for free. Make sure to keep your `AccessKey` secret.
        Signup or Login to [Picovoice Console](https://console.picovoice.ai/) to get your `AccessKey`.
        
        ## Overview
        
        Eagle consists of two distinct steps: Enrollment and Recognition. In the enrollment step, Eagle analyzes a series of
        utterances from a particular speaker to learn their unique voiceprint. This step results in an `EagleProfile` object,
        which can be stored and utilized during inference. During the Recognition step, Eagle compares the incoming frames of
        audio to the voiceprints of all enrolled speakers in real-time to determine the similarity between them.
        
        ## Microphone Demo
        
        The microphone demo captures audio input from a microphone that is connected. To run the demo, use the following command
        in the terminal:
        
        ```console
        eagle_demo_mic {enroll, test} --access_key ${ACCESS_KEY} ...
        ```
        
        Replace `${ACCESS_KEY}` with yours obtained from Picovoice Console.
        
        The commands `enroll` and `test` are used to create a speaker profile and perform speaker recognition, respectively.
        Detailed explanations of these commands will be provided in their respective sections.
        
        Furthermore, the demo offers optional arguments, which can be accessed by utilizing the `--help` argument. By doing so,
        you will receive a comprehensive listing of the available arguments along with their corresponding descriptions.
        
        ```console
        eagle_demo_mic --help
        ```
        
        ### Speaker Enrollment
        
        If the demo is executed in the enrollment mode by using the `enroll` command, it will initiate the enrollment process
        using the audio captured from the microphone. It will display the progress percentage in the terminal until it reaches
        100%. Once completed, it will save the profile of the enrolled speaker to the disk.
        
        ```console
        eagle_demo_mic enroll --access_key ${ACCESS_KEY} --output_profile_path ${OUTPUT_PROFILE_PATH}
        ``````
        
        Replace `${OUTPUT_PROFILE_PATH}` with the absolute path where the generated profile should be written.
        
        ### Speaker Recognition
        
        Once the speaker profile for all speakers are created, the demo can be run in the `test` mode by running the following
        command:
        
        ```console
        eagle_demo_mic test --access_key ${ACCESS_KEY} --input_profile_paths ${INPUT_PROFILE_PATH_1 ...}
        ```
        
        In this mode, you can include multiple speaker profiles by specifying them with the `--input_profile_paths` option.
        Eagle will assess and provide a distinct score for each profile, which will be displayed in the terminal.
        
        ## File Demo
        
        Similar to the mic demo, the file demo can be run in two modes: `enroll` and `test`
        
        ```console
        eagle_demo_file {enroll,test} --access_key ${ACCESS_KEY} ...
        ```
        
        Replace `${ACCESS_KEY}` with yours obtained from Picovoice Console.
        
        The commands `enroll` and `test` are used to create a speaker profile and perform speaker recognition, respectively, and
        will be discussed in detail in their respective sections.
        
        To view the optional arguments for the demo, use the `--help` argument. This will display a list of available arguments
        and their descriptions.
        
        ```console
        eagle_demo_file --help
        ```
        
        ### Speaker Enrollment
        
        To run the demo in `enroll` mode, you need two additional input arguments along with the AccessKey.
        
        ```console
        eagle_demo_file enroll --access_key ${ACCESS_KEY} \
          --output_profile_path ${OUTPUT_PROFILE_PATH} --enroll_audio_paths ${ENROLL_AUDIO_PATH_1 ...} 
        ```
        
        In this command, `{ENROLL_AUDIO_PATH_1 ...}` represents the absolute paths to the enroll audio files. If multiple files
        are provided, Eagle will process all of them. Once the specified files are processed, the demo will generate a profile at
        `${OUTPUT_PROFILE_PATH}`.
        
        ### Speaker Recognition
        
        The file demo requires a test audio and one or more speaker profiles that were created during the enrollment step.
        
        To run the demo, use the following command in the console:
        
        ```console
        eagle_demo_file test --access_key ${ACCESS_KEY} \
          --input_profile_paths ${INPUT_PROFILE_PATH_1 ...} --test_audio_path ${TEST_AUDIO_PATH}
        ```
        
        The demo will display the result for each enrolled speaker in the terminal.
        
        Optionally, you can also generate a `.csv` file for further analysis by including the `--csv_output_path` parameter:
        
        ```console
        eagle_demo_file test --access_key ${ACCESS_KEY} \
          --input_profile_paths ${INPUT_PROFILE_PATH_1 ...} --test_audio_path ${TEST_AUDIO_PATH} \
          --csv_output_path ${CSV_OUTPUT_PATH}
        ```
Keywords: Speaker Recognition,Speaker Identification,Voice Recognition,Voice Identification
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Multimedia :: Sound/Audio :: Speech
Requires-Python: >=3.5
Description-Content-Type: text/markdown
