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TODO:

  • Design directory structure
  • Usage
- Laronix_AUTOMOS
    - data
        - Template
            - ref_wav/
                - 1.wav
                - 2.wav
                - ...
            - ref_txt.txt
            - ref.csv # audio prosody features reference <generate by script>
    - exp
        - Template
            - Audio_to_evaluate # RAW WAV DATA
            - log.csv # Recording log 
            - output # wav.file  <generate by script>
    - model
        - epoch=3-step=7459.ckpt # MOS estimate model
        - wav2vec_small.pt # WER model
    - local
        - get_ref_PPM.py # script for generating data/<ref_dir>/ref.csv
        - post_processing.py # script for generating exp/<ref_dir>/output/*.wav

title: Laronix Automos emoji: 🏃 colorFrom: blue colorTo: blue sdk: gradio sdk_version: 3.2 app_file: app.py pinned: false license: afl-3.0

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Laronix_AutoMOS

Usage:

Step 1: Prepare data and text

<todo>

Step 2: Preprocessing

## Generating *.csv, Voice/Unvoice Plot (optional) and config (optional)
python local/get_ref_PPM.py --ref_txt <ref_text> \
                            --ref_wavs <ref_wavs> \
                            --output_dir <output_dir> \
                            --to_config <True/False> \
                            --UV_flag <True/False> \
                            --UV_thre <UV_thre>}

Step 3: Launch recording session:

## Start app.py
python app.py <config.yaml>
  • Find logging below and lick URL to start
Launch examples
Running on local URL:  http://127.0.0.1:7860/
...
    (Logs...)
...
Running on public URL: https://87abe771e93229da.gradio.app

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  • Python 100.0%
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