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app.py

@@ -1,33 +1,125 @@
+
 import streamlit as st
-from gtts import gTTS
-from scipy.io.wavfile import read
+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
-import matplotlib.pyplot as plt
-import io
-
-st.title('Comparing text to sound')
-
-texto1 = st.text_input('Text 1')
-texto2 = st.text_input('Text 2')
-
-if st.button('Generate plots'):
-    if texto1 and texto2:
-        tts1 = gTTS(texto1, lang='en')
-        fp1 = io.BytesIO()
-        tts1.save(fp1)
-        fp1.seek(0)
-        fs1, data1 = read(fp1)
-
-        tts2 = gTTS(texto2, lang='en')
-        fp2 = io.BytesIO()
-        tts2.save(fp2)
-        fp2.seek(0)
-        fs2, data2 = read(fp2)
-
-        fig, ax = plt.subplots()
-        ax.plot(data1, label='Text 1')
-        ax.plot(data2, label='Text 2')
-        ax.legend()
-        st.pyplot(fig)
-    else:
-        st.warning('Please add two texts.')
+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')
+texto2 = st.text_input('Second text')
+
+intercambiar = st.selectbox('Interchange texts', [False, True])
+
+if intercambiar:
+    texto1, texto2 = texto2, texto1
+
+if texto1=="":
+        texto1="a"
+
+if texto2=="":
+        texto2="a"
+
+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)
+
+

requirements.txt

@@ -1,5 +1,5 @@
 streamlit
-gtts
+pyttsx3
 scipy
-numpy
-matplotlib
+plotly
+numpy