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import numpy as np
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import matplotlib.pyplot as plt
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import librosa.display
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import librosa
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def calculate_features(y, sr):
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stft = np.abs(librosa.stft(y))
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duration = librosa.get_duration(y=y, sr=sr)
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cent = librosa.feature.spectral_centroid(S=stft, sr=sr)[0]
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bw = librosa.feature.spectral_bandwidth(S=stft, sr=sr)[0]
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rolloff = librosa.feature.spectral_rolloff(S=stft, sr=sr)[0]
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return stft, duration, cent, bw, rolloff
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def plot_title(title):
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plt.suptitle(title, fontsize=16, fontweight="bold")
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def plot_spectrogram(y, sr, stft, duration, cmap="inferno"):
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plt.subplot(3, 1, 1)
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plt.imshow(
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librosa.amplitude_to_db(stft, ref=np.max),
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origin="lower",
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extent=[0, duration, 0, sr / 1000],
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aspect="auto",
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cmap=cmap,
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)
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plt.colorbar(format="%+2.0f dB")
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plt.xlabel("Time (s)")
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plt.ylabel("Frequency (kHz)")
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plt.title("Spectrogram")
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def plot_waveform(y, sr, duration):
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plt.subplot(3, 1, 2)
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librosa.display.waveshow(y, sr=sr)
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plt.xlabel("Time (s)")
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plt.ylabel("Amplitude")
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plt.title("Waveform")
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def plot_features(times, cent, bw, rolloff, duration):
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plt.subplot(3, 1, 3)
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plt.plot(times, cent, label="Spectral Centroid (kHz)", color="b")
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plt.plot(times, bw, label="Spectral Bandwidth (kHz)", color="g")
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plt.plot(times, rolloff, label="Spectral Rolloff (kHz)", color="r")
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plt.xlabel("Time (s)")
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plt.title("Spectral Features")
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plt.legend()
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def analyze_audio(audio_file, save_plot_path="logs/audio_analysis.png"):
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y, sr = librosa.load(audio_file)
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stft, duration, cent, bw, rolloff = calculate_features(y, sr)
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plt.figure(figsize=(12, 10))
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plot_title("Audio Analysis" + " - " + audio_file.split("/")[-1])
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plot_spectrogram(y, sr, stft, duration)
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plot_waveform(y, sr, duration)
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plot_features(librosa.times_like(cent), cent, bw, rolloff, duration)
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plt.tight_layout()
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if save_plot_path:
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plt.savefig(save_plot_path, bbox_inches="tight", dpi=300)
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plt.close()
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audio_info = f"""Sample Rate: {sr}\nDuration: {(
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str(round(duration, 2)) + " seconds"
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if duration < 60
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else str(round(duration / 60, 2)) + " minutes"
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)}\nNumber of Samples: {len(y)}\nBits per Sample: {librosa.get_samplerate(audio_file)}\nChannels: {"Mono (1)" if y.ndim == 1 else "Stereo (2)"}"""
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return audio_info, save_plot_path
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