navyaparesh commited on
Commit
e21f7ff
Β·
verified Β·
1 Parent(s): 4616acd

Rename app (2).py to app.py

Browse files
Files changed (1) hide show
  1. app (2).py β†’ app.py +8 -25
app (2).py β†’ app.py RENAMED
@@ -45,10 +45,9 @@ This Gradio demo showcases **IndicConformer**, a speech recognition model for **
45
  #### **How to Use:**
46
  1. **Upload or record** an audio clip in any supported Indian language.
47
  2. Select the **mode** (CTC or RNNT) for transcription.
48
- 3. Click **"Transcribe"** to generate the corresponding text in the target language.
49
  4. View or copy the output for further use.
50
 
51
- πŸš€ Try it out and experience seamless speech recognition for Indian languages!
52
  """
53
 
54
  hf_token = os.getenv("HF_TOKEN")
@@ -62,8 +61,8 @@ model.eval()
62
  CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1" and torch.cuda.is_available()
63
 
64
  AUDIO_SAMPLE_RATE = 16000
65
- MAX_INPUT_AUDIO_LENGTH = 60 # in seconds
66
- DEFAULT_TARGET_LANGUAGE = "Bengali"
67
 
68
  @spaces.GPU
69
  def run_asr_ctc(input_audio: str, target_language: str) -> str:
@@ -156,14 +155,6 @@ with gr.Blocks() as demo_asr_ctc:
156
  btn = gr.Button("Transcribe")
157
  with gr.Column():
158
  output_text = gr.Textbox(label="Transcribed text")
159
-
160
- gr.Examples(
161
- examples=[
162
- ["assets/Bengali.wav", "Bengali", "English"],
163
- ["assets/Gujarati.wav", "Gujarati", "Hindi"],
164
- ["assets/Punjabi.wav", "Punjabi", "Hindi"],
165
-
166
- ],
167
  inputs=[input_audio, target_language],
168
  outputs=output_text,
169
  fn=run_asr_ctc,
@@ -191,14 +182,6 @@ with gr.Blocks() as demo_asr_rnnt:
191
  btn = gr.Button("Transcribe")
192
  with gr.Column():
193
  output_text = gr.Textbox(label="Transcribed text")
194
-
195
- gr.Examples(
196
- examples=[
197
- ["assets/Bengali.wav", "Bengali", "English"],
198
- ["assets/Gujarati.wav", "Gujarati", "Hindi"],
199
- ["assets/Punjabi.wav", "Punjabi", "Hindi"],
200
-
201
- ],
202
  inputs=[input_audio, target_language],
203
  outputs=output_text,
204
  fn=run_asr_rnnt,
@@ -216,11 +199,11 @@ with gr.Blocks() as demo_asr_rnnt:
216
 
217
  with gr.Blocks(css="style.css") as demo:
218
  gr.Markdown(DESCRIPTION)
219
- gr.DuplicateButton(
220
- value="Duplicate Space for private use",
221
- elem_id="duplicate-button",
222
- visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
223
- )
224
 
225
  with gr.Tabs():
226
  with gr.Tab(label="CTC"):
 
45
  #### **How to Use:**
46
  1. **Upload or record** an audio clip in any supported Indian language.
47
  2. Select the **mode** (CTC or RNNT) for transcription.
48
+ 3. Click **"Transcribe"** to generate the corresponding text.
49
  4. View or copy the output for further use.
50
 
 
51
  """
52
 
53
  hf_token = os.getenv("HF_TOKEN")
 
61
  CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1" and torch.cuda.is_available()
62
 
63
  AUDIO_SAMPLE_RATE = 16000
64
+ MAX_INPUT_AUDIO_LENGTH = 600 # in seconds
65
+ DEFAULT_TARGET_LANGUAGE = "Hindi"
66
 
67
  @spaces.GPU
68
  def run_asr_ctc(input_audio: str, target_language: str) -> str:
 
155
  btn = gr.Button("Transcribe")
156
  with gr.Column():
157
  output_text = gr.Textbox(label="Transcribed text")
 
 
 
 
 
 
 
 
158
  inputs=[input_audio, target_language],
159
  outputs=output_text,
160
  fn=run_asr_ctc,
 
182
  btn = gr.Button("Transcribe")
183
  with gr.Column():
184
  output_text = gr.Textbox(label="Transcribed text")
 
 
 
 
 
 
 
 
185
  inputs=[input_audio, target_language],
186
  outputs=output_text,
187
  fn=run_asr_rnnt,
 
199
 
200
  with gr.Blocks(css="style.css") as demo:
201
  gr.Markdown(DESCRIPTION)
202
+ # gr.DuplicateButton(
203
+ # value="Duplicate Space for private use",
204
+ # elem_id="duplicate-button",
205
+ # visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
206
+ # )
207
 
208
  with gr.Tabs():
209
  with gr.Tab(label="CTC"):