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Sophisticated audio matching and mastering node with advanced control for precise audio track alignment and tuning.
MatcheringAdvanced is a sophisticated node designed for audio matching and mastering, providing advanced capabilities to fine-tune audio tracks by aligning them with a reference track. This node is part of the Matchering library, which is renowned for its ability to match the sound characteristics of a target audio file to those of a reference file, ensuring consistency and quality in audio production. The advanced version of Matchering offers more granular control over the matching process, allowing you to adjust various parameters to achieve the desired audio output. This node is particularly beneficial for audio engineers and AI artists who require precise control over the audio mastering process, enabling them to produce professional-quality audio that meets specific standards and preferences.
The target
parameter represents the audio file that you want to process and match to the reference audio. It is crucial as it determines the audio characteristics that will be adjusted to align with the reference. The target audio should be in a compatible format and of sufficient quality to ensure effective matching.
The reference
parameter is the audio file that serves as the benchmark for matching. It provides the desired audio characteristics that the target audio will be adjusted to match. The reference audio should be carefully selected to represent the sound quality and style you aim to achieve in the target audio.
The internal_sample_rate
parameter specifies the sample rate at which the audio processing will occur internally. This affects the precision and quality of the audio processing, with higher sample rates generally providing better quality but requiring more computational resources.
The max_length
parameter defines the maximum length of the audio segment to be processed. This is important for managing processing time and resources, especially when dealing with long audio files. It ensures that only a specified portion of the audio is processed, which can be useful for focusing on specific sections.
The max_piece_size
parameter sets the maximum size of the audio pieces that will be analyzed during the matching process. This affects the granularity of the analysis, with smaller pieces allowing for more detailed adjustments but potentially increasing processing time.
The threshold
parameter determines the sensitivity of the matching process, affecting how closely the target audio will be adjusted to match the reference. A lower threshold may result in more aggressive matching, while a higher threshold may preserve more of the target's original characteristics.
The min_value
parameter sets the minimum value for certain processing operations, ensuring that the audio does not fall below a specified level. This can help maintain audio quality and prevent unwanted artifacts during processing.
The fft_size
parameter specifies the size of the Fast Fourier Transform (FFT) used in the analysis. This affects the frequency resolution of the analysis, with larger FFT sizes providing more detailed frequency information but requiring more computational power.
The lin_log_oversampling
parameter controls the oversampling method used during processing, which can affect the accuracy and quality of the audio matching. Different oversampling methods may be more suitable for different types of audio content.
The rms_correction_steps
parameter defines the number of steps used in the RMS (Root Mean Square) correction process. This affects the precision of the loudness matching between the target and reference audio, with more steps providing finer adjustments.
The clipping_samples_threshold
parameter sets the threshold for detecting clipping in the audio. This is important for preventing distortion and ensuring that the audio remains within acceptable levels during processing.
The limited_samples_threshold
parameter determines the threshold for limiting samples in the audio, helping to control the dynamic range and prevent excessive loudness.
The allow_equality
parameter specifies whether the matching process should allow for equal levels between the target and reference audio. This can be useful for maintaining consistency in certain audio characteristics.
The lowess_frac
parameter controls the fraction of data used in the LOWESS (Locally Weighted Scatterplot Smoothing) smoothing process. This affects the smoothness of the adjustments made to the audio, with higher fractions providing smoother results.
The lowess_it
parameter specifies the number of iterations used in the LOWESS smoothing process. More iterations can result in smoother adjustments but may increase processing time.
The lowess_delta
parameter sets the delta value for the LOWESS smoothing process, affecting the sensitivity of the smoothing. This can influence how closely the adjustments follow the original audio characteristics.
The limiter_config
parameter allows you to specify a custom configuration for the limiter used in the audio processing. This can be used to fine-tune the limiting behavior to suit specific audio content and preferences.
The Result
output provides the final processed audio, with all matching and mastering adjustments applied. This is the main output that reflects the desired audio characteristics based on the reference.
The Result (no limiter)
output provides the processed audio without any limiting applied. This can be useful for further processing or analysis where limiting is not desired.
The Result (no limiter, normalized)
output provides the processed audio without limiting, but with normalization applied. This ensures that the audio levels are consistent and suitable for playback or further processing.
fft_size
and rms_correction_steps
values to find the optimal balance between processing time and audio quality.limiter_config
parameter to customize the limiting behavior, especially if you are working with audio that has a wide dynamic range.fft_size
settings.max_length
or fft_size
parameters to decrease processing time, or consider processing smaller segments of the audio.RunComfy is the premier ComfyUI platform, offering ComfyUI online environment and services, along with ComfyUI workflows featuring stunning visuals. RunComfy also provides AI Playground, enabling artists to harness the latest AI tools to create incredible art.