In this blog post, we will explore how to detect audio clipping in Python using the pydub library. Audio clipping refers to the distortion that occurs when the volume of an audio signal exceeds the maximum level that can be accurately represented. Detecting clipping in audio files can help in identifying potential issues or improving the audio quality.

Install pydub

Before we begin, make sure you have pydub installed. You can install it using pip:

pip install pydub

Loading the Audio File

Let’s assume we have an audio file that we want to analyze for clipping. We’ll start by loading the audio file using pydub:

from pydub import AudioSegment

audio_file = "path/to/audio/file.mp3"  # replace with your audio file path

audio = AudioSegment.from_file(audio_file)

Checking for Clipping

To check for clipping in the audio file, we can iterate over the audio samples and compare them against a threshold value. If a sample exceeds the threshold, we can consider it as clipped.

clip_threshold = 0.9  # adjust the threshold value to your requirements
clipped_samples = []

for sample in audio:
    if abs(sample) >= clip_threshold:
        clipped_samples.append(sample)

In the above code, we use a clip threshold value of 0.9, but you can adjust it based on the requirements of your audio analysis.

Analyzing Clipping

Once we have identified the clipped samples, we can analyze them further to gather more insights. For example, we can calculate the percentage of samples that are clipped in the audio file:

total_samples = len(audio)
percentage_clipped = (len(clipped_samples) / total_samples) * 100

Visualizing Clipping

To visualize the clipping in the audio file, we can plot the clipped samples on a waveform graph. Here’s an example using matplotlib:

import matplotlib.pyplot as plt
import numpy as np

plt.plot(np.arange(len(audio)), audio)
plt.scatter(np.arange(len(clipped_samples)), clipped_samples, color='red')
plt.xlabel("Sample")
plt.ylabel("Amplitude")
plt.title("Audio Clipping")
plt.show()

The above code will plot the entire audio waveform with clipped samples marked in red.

Conclusion

In this blog post, we explored how to detect audio clipping in Python using the pydub library. We learned how to load an audio file, check for clipping, analyze the result, and visualize the findings. Detecting and analyzing audio clipping can be helpful in various audio processing tasks, such as audio restoration or quality assessment.