Visualise waveform and spectrogram using Librosa

gistfile1.txt

# display one audio waveform in time domain
def plot_waveform(audio_file_path):
    # # Your code goes here (do not change the function definition)

    plt.figure(figsize=(12, 4))

    waveform, sample_rate = librosa.load(audio_file_path, sr=None)

    librosa.display.waveshow(waveform, sr=sample_rate, color="orange")
    plt.title("Waveform of " + str(audio_file_path.split("/")[-1]))
    plt.grid(True)
    plt.xlabel("Time (s)")
    plt.ylabel("Amplitude")
    plt.show()


# extract one spectrogram for one audio sample and display ####
def build_spectogram(file_path):
    plt.interactive(False)
    plt.figure(figsize=(12, 4))

    # Your code goes here (do not change the function definition)
    y, sr = librosa.load(file_path, sr=None)

    stft = librosa.stft(y, hop_length=256)
    stft_db = librosa.amplitude_to_db(np.abs(stft), ref=np.max)
    librosa.display.specshow(
        stft_db, sr=sr, x_axis="time", y_axis="log", cmap="inferno"
    )

    plt.colorbar()
    plt.title("Spectrogram of " + str(file_path.split("/")[-1]))
    plt.tight_layout()
    plt.show()