Modified app.py

app.py

@@ -60,14 +60,11 @@ def predict(text, speaker):
 title = "Text-to-Speech based on SpeechT5"
 
 description = """
-The <b>SpeechT5</b> model is pre-trained on text as well as speech inputs, with targets that are also a mix of text and speech.
-By pre-training on text and speech at the same time, it learns unified representations for both, resulting in improved modeling capabilities.
+The <b>SpeechT5</b> model is pre-trained on text as well as speech inputs, with targets that are also a mix of text and speech. By pre-training on text and speech at the same time, it learns unified representations for both, resulting in improved modeling capabilities.
 
 This space demonstrates the <b>text-to-speech</b> (TTS) checkpoint for the English language.
 
-<b>How to use:</b> Enter some English text and choose a speaker. The output is a mel spectrogram, which is converted to a mono 16 kHz waveform by the
-HiFi-GAN vocoder. Because the model always applies random dropout, each attempt will give slightly different results.
-The <em>Surprise Me!</em> option creates a completely randomized speaker.
+<b>How to use:</b> Enter some English text and choose a speaker. The output is a mel spectrogram, which is converted to a mono 16 kHz waveform by the HiFi-GAN vocoder. Because the model always applies random dropout, each attempt will give slightly different results. The <em>Surprise Me!</em> option creates a completely randomized speaker.
 """
 
 article = """