Export Frequency Spectrum from Audacity to Text

Audacity provides a built-in frequency analysis tool that allows researchers to calculate the Fast Fourier Transform (FFT) of an audio signal and export the resulting spectral data into a plain text file. This exported data contains discrete frequency bins paired with their corresponding amplitude values in decibels, making it ideal for quantitative analysis in external mathematical environments such as MATLAB, Python, R, or spreadsheet software.

Step 1: Select the Audio Region

1. Open your audio file in Audacity.
2. Using the Selection Tool (F1), highlight the specific segment of the waveform you need to analyze.
3. For consistent scientific measurements, ensure the selection length matches your experimental parameters, as varying lengths can influence spectral resolution depending on the FFT window chosen.

Step 2: Open the Frequency Analysis Window

1. Navigate to the top menu and select Analyze > Plot Spectrum....
2. A separate window titled "Frequency Analysis" will appear, displaying a visual graph of the spectral distribution for the selected audio range.

Step 3: Configure Analysis Parameters

Before exporting, adjust the parameters at the bottom of the window to meet your scientific requirements:

• Algorithm: Set to Spectrum for standard Fourier transform analysis.
• Function (Window): Choose an appropriate windowing function. Hanning or Hamming are standard for general acoustic measurements, while Rectangular is useful for transient signals.
• Size: Choose the FFT size (e.g., 512, 1024, 2048, up to 65536). A larger size yields higher frequency resolution (narrower bins) at the cost of temporal specificity.
• Axis: Choose between Log frequency or Linear frequency depending on your visualization preference; note that this setting only changes the visual graph, not the raw exported numerical values.

Step 4: Export the Data to a Text File

1. Click the Export... button in the lower-right corner of the Frequency Analysis window.
2. In the file dialog, choose your destination directory and enter a filename.
3. Ensure the file extension is set to .txt (e.g., spectrum_data.txt).
4. Click Save.

Step 5: Structure of the Exported Data

The resulting text file is formatted as tab-delimited plain text with two columns:

• Column 1: Frequency in Hertz (Hz).
• Column 2: Amplitude in Decibels (dBFS), relative to full scale.

This format can be directly imported into scientific software. For example, in Python using NumPy or Pandas, you can load the data using numpy.loadtxt('spectrum_data.txt', skiprows=1) or pandas.read_csv('spectrum_data.txt', sep='\t').