Update app.py

app.py

@@ -182,25 +182,25 @@ 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.
 
-SpeechT5 can be fine-tuned for different speech tasks. This space demonstrates the <b>text-to-speech</b> (TTS) checkpoint for the English language.
+SpeechT5 can be fine-tuned for different speech tasks. This space demonstrates the <b>text-to-speech</b> (TTS) checkpoint for the Armenian language.
 
 See also the <a href="https://huggingface.co/spaces/Matthijs/speecht5-asr-demo">speech recognition (ASR) demo</a>
 and the <a href="https://huggingface.co/spaces/Matthijs/speecht5-vc-demo">voice conversion demo</a>.
 
 Refer to <a href="https://colab.research.google.com/drive/1i7I5pzBcU3WDFarDnzweIj4-sVVoIUFJ">this Colab notebook</a> to learn how to fine-tune the SpeechT5 TTS model on your own dataset or 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
+<b>How to use:</b> Enter some Armenian 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.
 """
 
 examples = [
-    ["It is not in the stars to hold our destiny but in ourselves.", "BDL (male)"],
-    ["The octopus and Oliver went to the opera in October.", "CLB (female)"],
-    ["She sells seashells by the seashore. I saw a kitten eating chicken in the kitchen.", "RMS (male)"],
-    ["Brisk brave brigadiers brandished broad bright blades, blunderbusses, and bludgeons—balancing them badly.", "SLT (female)"],
-    ["A synonym for cinnamon is a cinnamon synonym.", "BDL (male)"],
-    ["How much wood would a woodchuck chuck if a woodchuck could chuck wood? He would chuck, he would, as much as he could, and chuck as much wood as a woodchuck would if a woodchuck could chuck wood.", "CLB (female)"],
+    ["Մեր ճակատագիրը աստղերի մեջ չէ, այլ մեր մեջ:", "BDL (male)"],
+    ["Հոկտեմբերին ութոտնուկն ու Օլիվերը գնացին օպերա։", "BDL (male)],
+    ["Նա ծովի ափին ծովախեցգետիններ է վաճառում: Ես տեսա, որ խոհանոցում հավ է ուտում մի ձագ:", "BDL (male)],
+    ["Կտրուկ խիզախ բրիգադները թափահարում էին լայն, պայծառ շեղբեր, կոպիտ ավտոբուսներ և մռութներ՝ վատ հավասարակշռելով դրանք:", "BDL (male)],
+    ["Դարչինի հոմանիշը դարչինի հոմանիշն է:", "BDL (male)"],
+    ["Ինչքա՞ն փայտ կթափի փայտափայտը, եթե փայտափայտը կարողանար փայտ ծակել: Նա կխփեր, կաներ, այնքան, որքան կարող էր, և այնքան փայտ կխփեր, որքան փայտափայտը, եթե փայտափայտը կարողանար փայտ ծակել:", "BDL (male)],
 ]
 
 gr.Interface(