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Sophisticated audio upscaling node enhancing clarity and detail for high-resolution playback using advanced resampling techniques.
EgregoraAudioUpscaler is a sophisticated node designed to enhance audio quality by increasing the sample rate of audio files, a process known as upscaling. This node is particularly beneficial for improving the clarity and detail of audio tracks, making them suitable for high-resolution playback systems. By utilizing advanced resampling techniques, EgregoraAudioUpscaler ensures that the audio retains its original quality while being transformed to a higher sample rate. This process is crucial for audio professionals and enthusiasts who seek to maintain the integrity of their audio content while adapting it to different playback environments. The node intelligently selects the most appropriate resampling method based on the available libraries, ensuring optimal performance and quality.
The audio parameter is the primary input for the EgregoraAudioUpscaler node, representing the audio data that you wish to upscale. This parameter is crucial as it contains the audio samples and metadata necessary for processing. The quality and characteristics of the input audio will directly affect the outcome of the upscaling process.
The target_sr parameter specifies the target sample rate to which the audio should be upscaled. By default, this is set to 48000 Hz, a common sample rate for high-quality audio. Adjusting this parameter allows you to tailor the upscaling process to meet specific requirements, such as preparing audio for different playback systems or formats.
The mode parameter determines the resampling method used during the upscaling process. It defaults to "auto," which automatically selects the best available method based on the installed libraries. Options include "scipy_polyphase," "torchaudio," and "linear," each offering different levels of quality and computational efficiency. Selecting the appropriate mode can significantly impact the quality and speed of the upscaling process.
The kaiser_beta parameter is used when the "torchaudio" resampling method is selected. It controls the beta parameter of the Kaiser window, affecting the trade-off between the main lobe width and the side lobe level in the frequency response. The default value is 14.769, which provides a good balance for most applications. Adjusting this parameter can fine-tune the resampling process to achieve the desired audio quality.
The audio output parameter contains the upscaled audio data, now at the specified target sample rate. This output is crucial for further processing or playback, as it represents the enhanced version of the original audio input. The quality of this output depends on the input parameters and the selected resampling method.
mode settings to find the optimal balance between quality and processing time for your specific use case.kaiser_beta parameter to fine-tune the audio quality when using the "torchaudio" resampling method.pip install scipy and try running the node again.pip install torchaudio and re-run the node.target_sr parameter is set to a non-positive value.target_sr parameter is set to a positive integer, such as 48000, and try again.RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Models, enabling artists to harness the latest AI tools to create incredible art.