Adjusting app

app.py

@@ -98,14 +98,6 @@ demo = gr.Blocks()
 transcribe = gr.Interface(
     fn=transcribe,
     inputs=[
-        # gr.Markdown(
-        #     """
-        #     Test Latvian speech recognition (STT) models. Three models are available:
-        #     * [tiny](https://huggingface.co/RaivisDejus/whisper-tiny-lv) - Fastest, requiring least RAM, but also least accurate
-        #     * [small](https://huggingface.co/RaivisDejus/whisper-small-lv) - Reasonably fast, reasonably accurate, requiring reasonable amounts of RAM
-        #     * [large](https://huggingface.co/AiLab-IMCS-UL/whisper-large-v3-lv-late-cv17) - Most accurate, developed by scientists from [ailab.lv](https://ailab.lv/). Requires most RAM and for best performance should be run on a GPU.
-        #     """
-        # ),
         gr.Dropdown([
             ("tiny", "RaivisDejus/whisper-tiny-lv"),
             ("small", "RaivisDejus/whisper-small-lv"),
@@ -114,7 +106,7 @@ transcribe = gr.Interface(
         gr.Audio(sources=["upload", "microphone"],type="filepath", label="Audio"),
         gr.Radio([("Transcribe", "transcribe"), ("Translate to English", "translate",)], label="Task", value="transcribe"),
     ],
-    outputs=gr.Textbox(label="Transcription", lines=10),
+    outputs=gr.Textbox(label="Transcription", lines=15),
     title="Latvian speech recognition: Transcribe Audio",
     description=("""
         Test Latvian speech recognition (STT) models. Three models are available:
@@ -124,6 +116,8 @@ transcribe = gr.Interface(
         * [small](https://huggingface.co/RaivisDejus/whisper-small-lv) - Reasonably fast, reasonably accurate, requiring reasonable amounts of RAM
         
         * [large](https://huggingface.co/AiLab-IMCS-UL/whisper-large-v3-lv-late-cv17) - Most accurate, developed by scientists from [ailab.lv](https://ailab.lv/). Requires most RAM and for best performance should be run on a GPU.
+        
+        To improve speech recognition quality, more data is needed, donate your voice on [Balsu talka](https://balsutalka.lv/)
         """
     ),
     allow_flagging="never",
@@ -142,8 +136,17 @@ yt_transcribe = gr.Interface(
     ],
     outputs=["html", "text"],
     title="Latvian speech recognition: Transcribe YouTube",
-    description=(
-        "Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
+    description=("""
+        Test Latvian speech recognition (STT) models. Three models are available:
+
+        * [tiny](https://huggingface.co/RaivisDejus/whisper-tiny-lv) - Fastest, requiring least RAM, but also least accurate
+
+        * [small](https://huggingface.co/RaivisDejus/whisper-small-lv) - Reasonably fast, reasonably accurate, requiring reasonable amounts of RAM
+
+        * [large](https://huggingface.co/AiLab-IMCS-UL/whisper-large-v3-lv-late-cv17) - Most accurate, developed by scientists from [ailab.lv](https://ailab.lv/). Requires most RAM and for best performance should be run on a GPU.
+
+        To improve speech recognition quality, more data is needed, donate your voice on [Balsu talka](https://balsutalka.lv/)
+        """
     ),
     allow_flagging="never",
 )