![]() ![]() For example a ballad with slow background music and a strong female voice can get an accuracy of over 90%, while a rock song with loud background music and a rough male voice can drop below 30%. The precision of this method changes greatly with the analyzed audio. Details for building your own model can be found in the dev/ folder. The deep learning model was trained on a large karaoke database. The predicted pitches are reevaluated to match the pseudo key. Statistical postprocessing is used to determine pseudo key of the song. The output is then fed into a neuronal network to determine the pitches. These chunks are divided into blocks to be transformed into features. The song is converted into a mono wav and gets split into the predefined audio segments. The software takes a timed usdx project file and the corresponding audio file. Just execute the following command within the cmd/powershell: The default would be "ffmpeg\bin\ffmpeg.exe" within the project root directory. To include ffmpeg into the binary, it needs to be placed as specified by the setup.spec file. To achieve this, an additional package has to be installed. The software can be compiled into a single standalone binary. ![]() Sudo apt-get install python3 python3-pip ffmpegĬommand line options for nono graphical execution: flagĭeveloper information build instructions (windows only) Pip install ultrastar-pitch linux (debian) If you want to use the python application do the following: windows In case of an error, try to install Microsoft Visual C Redistributable 圆4 (2010 2015). If you are using the binary, everything should run out of the box.
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