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| import streamlit as st | |
| import pyttsx3 | |
| from scipy.io import wavfile | |
| from scipy import signal | |
| from scipy.spatial import distance | |
| import plotly.graph_objs as go | |
| import numpy as np | |
| from scipy.interpolate import interp2d | |
| def similarity(file1, file2): | |
| fs1, data1 = wavfile.read(file1) | |
| fs2, data2 = wavfile.read(file2) | |
| f1, t1, Sxx1 = signal.spectrogram(data1, fs=fs1) | |
| f2, t2, Sxx2 = signal.spectrogram(data2, fs=fs2) | |
| interp1 = interp2d(t1, f1, Sxx1) | |
| interp2 = interp2d(t2, f2, Sxx2) | |
| tmin = max(t1.min(), t2.min()) | |
| tmax = min(t1.max(), t2.max()) | |
| fmin = max(f1.min(), f2.min()) | |
| fmax = min(f1.max(), f2.max()) | |
| tnew = np.linspace(tmin, tmax, num=max(len(t1), len(t2))) | |
| fnew = np.linspace(fmin, fmax, num=max(len(f1), len(f2))) | |
| Sxx1new = interp1(tnew, fnew) | |
| Sxx2new = interp2(tnew, fnew) | |
| d = distance.euclidean(Sxx1new.flatten(), Sxx2new.flatten()) | |
| max_d = max(Sxx1new.max(), Sxx2new.max()) * len(Sxx1new.flatten()) | |
| return 100 * (1 - d / max_d) | |
| st.title('Text to Sound Comparing') | |
| texto1 = st.text_input('First text','hi') | |
| texto2 = st.text_input('Second text','five') | |
| intercambiar = st.selectbox('Interchange texts', [False, True]) | |
| if intercambiar: | |
| texto1, texto2 = texto2, texto1 | |
| if texto1=="": | |
| texto1="hi" | |
| if texto2=="": | |
| texto2="five" | |
| if 1: | |
| engine = pyttsx3.init() | |
| engine.setProperty('voice', 'english') | |
| engine.save_to_file(texto1, 'texto1.wav') | |
| engine.save_to_file(texto2, 'texto2.wav') | |
| engine.runAndWait() | |
| fs1, data1 = wavfile.read('texto1.wav') | |
| fs2, data2 = wavfile.read('texto2.wav') | |
| inicio1 = st.slider('Start 1: '+str(texto1), 0, len(data1), 0) | |
| inicio2 = st.slider('Start 2: '+str(texto2), 0, len(data2), 0) | |
| f1, t1, Sxx1 = signal.spectrogram(data1[inicio1:], fs=fs1) | |
| f2, t2, Sxx2 = signal.spectrogram(data2[inicio2:], fs=fs2) | |
| fig1 = go.Figure() | |
| fig1.add_trace(go.Scatter(y=data1[inicio1:], mode='lines', name='Text 1: '+str(texto1))) | |
| fig1.add_trace(go.Scatter(y=data2[inicio2:], mode='lines', name='Text 2: '+str(texto2))) | |
| st.header('Waves') | |
| st.plotly_chart(fig1) | |
| fig2 = go.Figure() | |
| fig2.add_trace(go.Heatmap(x=t1, y=f1, z=Sxx1, name='Spectrogram 1', xaxis='x2', yaxis='y2')) | |
| st.header('Spectrogram '+str(texto1)) | |
| st.plotly_chart(fig2) | |
| fig3 = go.Figure() | |
| fig3.add_trace(go.Heatmap(x=t2, y=f2, z=Sxx2, name='Spectrogram 2', xaxis='x3', yaxis='y3')) | |
| st.header('Spectrogram '+str(texto2)) | |
| st.plotly_chart(fig3) | |
| #sim = similarity('texto1.wav', 'texto2.wav') | |
| #print(f'Similarity: {sim:.2f}%') | |
| #st.header('Similarity: '+str(sim)) | |
| N = len(data1[inicio1:]) | |
| T = 1.0 / fs1 | |
| yf = np.fft.fft(data1[inicio1:]) | |
| xf = np.linspace(0.0, 1.0/(2.0*T), N//2) | |
| fig4 = go.Figure() | |
| fig4.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 1: '+str(texto1))) | |
| st.header('Fourier '+str(texto1)) | |
| st.plotly_chart(fig4) | |
| N = len(data2[inicio2:]) | |
| T = 1.0 / fs2 | |
| yf = np.fft.fft(data2[inicio2:]) | |
| xf = np.linspace(0.0, 1.0/(2.0*T), N//2) | |
| fig5 = go.Figure() | |
| fig5.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 2: '+str(texto2))) | |
| st.header('Fourier '+str(texto2)) | |
| st.plotly_chart(fig5) | |
| N = len(data1[inicio1:]) | |
| T = 1.0 / fs1 | |
| yf = np.fft.fft(data1[inicio1:]) | |
| xf = np.linspace(0.0, 1.0/(2.0*T), N//2) | |
| fig6 = go.Figure() | |
| fig6.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 1: '+str(texto1))) | |
| N = len(data2[inicio2:]) | |
| T = 1.0 / fs2 | |
| yf = np.fft.fft(data2[inicio2:]) | |
| xf = np.linspace(0.0, 1.0/(2.0*T), N//2) | |
| fig6.add_trace(go.Scatter(x=xf, y=2.0/N * np.abs(yf[0:N//2]), mode='lines', name='Text 2: '+str(texto2))) | |
| st.header('Fourier Mix') | |
| st.plotly_chart(fig6) | |