python - librosa.load

Python - librosa.load

librosa.load is a function from the librosa library in Python, which is commonly used for audio analysis tasks, such as loading audio files. Here's how you can use librosa.load:

Usage of librosa.load

  1. Installation: Before using librosa.load, you need to install the librosa library. You can install it using pip:

    pip install librosa

  2. Loading an Audio File: To load an audio file using librosa.load, you typically provide the file path:

    import librosa

# Example file path
audio_file = 'path_to_your_audio_file.wav'  # Replace with your file path

# Load audio file
y, sr = librosa.load(audio_file)
    • y: The audio time series as a NumPy array.
    • sr: The sampling rate of y.

  3. Additional Parameters:

    • sr=None: By default, sr is set to None, which means librosa will use the native sampling rate of the audio file unless specified otherwise.

    • duration=None: Specifies the duration of audio to load, in seconds.

    • offset=0.0: Specifies the offset, in seconds, from the beginning of the file.

    • dtype=np.float32: Specifies the data type of y.

  4. Example: Here's a complete example showing how to load an audio file and print its duration:

    import librosa

# Example file path
audio_file = 'path_to_your_audio_file.wav'  # Replace with your file path

# Load audio file
y, sr = librosa.load(audio_file)

# Calculate duration in seconds
duration = librosa.get_duration(y=y, sr=sr)
print(f"Duration: {duration:.2f} seconds")

Notes

  • File Formats: librosa.load supports various audio file formats (e.g., WAV, MP3, FLAC) that are supported by the audioread library.

  • Audio Data: After loading, y represents the audio time series as a 1-dimensional NumPy array, and sr represents the sampling rate (samples per second).

  • Further Processing: Once loaded, you can use y and sr for various audio processing tasks such as feature extraction, analysis, and visualization.

  • Error Handling: Ensure the file path provided to librosa.load is correct and the file exists; otherwise, it will raise an FileNotFoundError.

By using librosa.load, you can easily load audio files into your Python environment for further analysis or processing tasks using the powerful capabilities provided by the librosa library. Adjust the parameters as per your specific needs and handle any exceptions that may arise during loading or processing.

Examples

  1. Python librosa.load: Basic Audio Loading Description: Load an audio file using librosa.load and print its sampling rate and duration.

    import librosa

# Load audio file
audio_path = 'path_to_your_audio_file.wav'
y, sr = librosa.load(audio_path)

# Print sampling rate and duration
print(f'Sampling rate: {sr} Hz')
print(f'Duration: {librosa.get_duration(y)} seconds')

  2. Python librosa.load: Load Audio with Offset and Duration Description: Load a segment of an audio file using librosa.load with specific offset and duration.

    import librosa

# Load audio file segment
audio_path = 'path_to_your_audio_file.wav'
offset = 10.0  # seconds
duration = 5.0  # seconds
y, sr = librosa.load(audio_path, offset=offset, duration=duration)

# Print sampling rate and duration of loaded segment
print(f'Sampling rate: {sr} Hz')
print(f'Duration: {librosa.get_duration(y)} seconds')

  3. Python librosa.load: Load Audio with Mono Conversion Description: Load an audio file and convert it to mono using librosa.load.

    import librosa

# Load audio file and convert to mono
audio_path = 'path_to_your_audio_file.wav'
y, sr = librosa.load(audio_path, mono=True)

# Print sampling rate and duration
print(f'Sampling rate: {sr} Hz')
print(f'Duration: {librosa.get_duration(y)} seconds')

  4. Python librosa.load: Load Audio with Resampling Description: Load an audio file and resample it to a different sampling rate using librosa.load.

    import librosa

# Load audio file and resample to target sampling rate
audio_path = 'path_to_your_audio_file.wav'
target_sr = 22050  # target sampling rate
y, sr = librosa.load(audio_path, sr=target_sr)

# Print actual sampling rate and duration
print(f'Original Sampling rate: {sr} Hz')
print(f'Duration: {librosa.get_duration(y)} seconds')

  5. Python librosa.load: Load Audio with Time-Series Normalization Description: Load an audio file and normalize its time-series using librosa.load.

    import librosa

# Load audio file and normalize time-series
audio_path = 'path_to_your_audio_file.wav'
y, sr = librosa.load(audio_path, norm=True)

# Print sampling rate and duration
print(f'Sampling rate: {sr} Hz')
print(f'Duration: {librosa.get_duration(y)} seconds')

  6. Python librosa.load: Load Audio with Offset and Duration in Frames Description: Load a segment of an audio file using frame-based offset and duration with librosa.load.

    import librosa

# Load audio file segment with frame-based offset and duration
audio_path = 'path_to_your_audio_file.wav'
offset_frames = 10000  # offset in frames
duration_frames = 5000  # duration in frames
y, sr = librosa.load(audio_path, offset=offset_frames, duration=duration_frames, sr=None)

# Print sampling rate and duration of loaded segment
print(f'Original Sampling rate: {sr} Hz')
print(f'Duration: {librosa.get_duration(y, sr=sr)} seconds')

  7. Python librosa.load: Load Audio and Handle Errors Description: Load an audio file with error handling for librosa.load exceptions.

    import librosa
import librosa.util.exceptions as librosa_exceptions

# Load audio file with error handling
audio_path = 'path_to_your_audio_file.wav'
try:
    y, sr = librosa.load(audio_path)
    print(f'Sampling rate: {sr} Hz')
    print(f'Duration: {librosa.get_duration(y)} seconds')
except (librosa_exceptions.ParameterError, FileNotFoundError) as e:
    print(f'Error loading audio file: {e}')

  8. Python librosa.load: Load Audio and Compute Spectrogram Description: Load an audio file and compute its spectrogram using librosa.load.

    import librosa
import librosa.display as librosa_display
import matplotlib.pyplot as plt

# Load audio file and compute spectrogram
audio_path = 'path_to_your_audio_file.wav'
y, sr = librosa.load(audio_path)
spectrogram = librosa.amplitude_to_db(librosa.stft(y), ref=np.max)

# Display spectrogram
plt.figure(figsize=(10, 4))
librosa_display.specshow(spectrogram, sr=sr, x_axis='time', y_axis='log')
plt.colorbar(format='%+2.0f dB')
plt.title('Spectrogram')
plt.show()

  9. Python librosa.load: Load Audio and Extract Mel-Frequency Cepstral Coefficients (MFCC) Description: Load an audio file and extract its Mel-Frequency Cepstral Coefficients (MFCC) using librosa.load.

    import librosa
import librosa.display as librosa_display
import matplotlib.pyplot as plt

# Load audio file and extract MFCC
audio_path = 'path_to_your_audio_file.wav'
y, sr = librosa.load(audio_path)
mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13)

# Display MFCC
plt.figure(figsize=(10, 4))
librosa_display.specshow(mfccs, x_axis='time')
plt.colorbar()
plt.title('MFCC')
plt.show()

  10. Python librosa.load: Load Audio and Perform Beat Tracking Description: Load an audio file and perform beat tracking using librosa.load.

    import librosa
import librosa.display as librosa_display
import matplotlib.pyplot as plt

# Load audio file and perform beat tracking
audio_path = 'path_to_your_audio_file.wav'
y, sr = librosa.load(audio_path)
tempo, beat_frames = librosa.beat.beat_track(y=y, sr=sr)

# Plot beat frames
plt.figure(figsize=(10, 4))
librosa_display.specshow(librosa.amplitude_to_db(librosa.stft(y)), x_axis='time', y_axis='log')
plt.vlines(librosa.frames_to_time(beat_frames, sr=sr), 0, 1, color='r', alpha=0.9, linestyle='--', label='Beats')
plt.colorbar(format='%+2.0f dB')
plt.title('Beat Tracking')
plt.legend()
plt.show()

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