Spaces:
Runtime error
Runtime error
Commit
Β·
a316967
1
Parent(s):
0a1595f
Add second example (#4)
Browse files- add second example (d101dad7e201f07bf8fb04dde60e0a0ac667b7cc)
Co-authored-by: Sanchit Gandhi <[email protected]>
- app.py +19 -5
- assets/sample_input_2.mp3 +3 -0
app.py
CHANGED
|
@@ -1,5 +1,6 @@
|
|
| 1 |
import os
|
| 2 |
|
|
|
|
| 3 |
import gradio as gr
|
| 4 |
import numpy as np
|
| 5 |
import torch
|
|
@@ -48,12 +49,12 @@ translator = Translator(
|
|
| 48 |
def predict(
|
| 49 |
task_name: str,
|
| 50 |
audio_source: str,
|
| 51 |
-
input_audio_mic: str
|
| 52 |
-
input_audio_file: str
|
| 53 |
-
input_text: str
|
| 54 |
-
source_language: str
|
| 55 |
target_language: str,
|
| 56 |
-
) -> tuple[tuple[int, np.ndarray]
|
| 57 |
task_name = task_name.split()[0]
|
| 58 |
source_language_code = LANGUAGE_NAME_TO_CODE.get(source_language, None)
|
| 59 |
target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
|
|
@@ -290,6 +291,8 @@ with gr.Blocks(css="style.css") as demo:
|
|
| 290 |
examples=[
|
| 291 |
["assets/sample_input.mp3", "French"],
|
| 292 |
["assets/sample_input.mp3", "Mandarin Chinese"],
|
|
|
|
|
|
|
| 293 |
],
|
| 294 |
inputs=[input_audio_file, target_language],
|
| 295 |
outputs=[output_audio, output_text],
|
|
@@ -301,6 +304,8 @@ with gr.Blocks(css="style.css") as demo:
|
|
| 301 |
examples=[
|
| 302 |
["assets/sample_input.mp3", "French"],
|
| 303 |
["assets/sample_input.mp3", "Mandarin Chinese"],
|
|
|
|
|
|
|
| 304 |
],
|
| 305 |
inputs=[input_audio_file, target_language],
|
| 306 |
outputs=[output_audio, output_text],
|
|
@@ -312,6 +317,10 @@ with gr.Blocks(css="style.css") as demo:
|
|
| 312 |
examples=[
|
| 313 |
["My favorite animal is the elephant.", "English", "French"],
|
| 314 |
["My favorite animal is the elephant.", "English", "Mandarin Chinese"],
|
|
|
|
|
|
|
|
|
|
|
|
|
| 315 |
],
|
| 316 |
inputs=[input_text, source_language, target_language],
|
| 317 |
outputs=[output_audio, output_text],
|
|
@@ -323,6 +332,10 @@ with gr.Blocks(css="style.css") as demo:
|
|
| 323 |
examples=[
|
| 324 |
["My favorite animal is the elephant.", "English", "French"],
|
| 325 |
["My favorite animal is the elephant.", "English", "Mandarin Chinese"],
|
|
|
|
|
|
|
|
|
|
|
|
|
| 326 |
],
|
| 327 |
inputs=[input_text, source_language, target_language],
|
| 328 |
outputs=[output_audio, output_text],
|
|
@@ -333,6 +346,7 @@ with gr.Blocks(css="style.css") as demo:
|
|
| 333 |
asr_examples = gr.Examples(
|
| 334 |
examples=[
|
| 335 |
["assets/sample_input.mp3", "English"],
|
|
|
|
| 336 |
],
|
| 337 |
inputs=[input_audio_file, target_language],
|
| 338 |
outputs=[output_audio, output_text],
|
|
|
|
| 1 |
import os
|
| 2 |
|
| 3 |
+
from typing import Union
|
| 4 |
import gradio as gr
|
| 5 |
import numpy as np
|
| 6 |
import torch
|
|
|
|
| 49 |
def predict(
|
| 50 |
task_name: str,
|
| 51 |
audio_source: str,
|
| 52 |
+
input_audio_mic: Union[str, None],
|
| 53 |
+
input_audio_file: Union[str, None],
|
| 54 |
+
input_text: Union[str, None],
|
| 55 |
+
source_language: Union[str, None],
|
| 56 |
target_language: str,
|
| 57 |
+
) -> tuple[Union[tuple[int, np.ndarray], None], str]:
|
| 58 |
task_name = task_name.split()[0]
|
| 59 |
source_language_code = LANGUAGE_NAME_TO_CODE.get(source_language, None)
|
| 60 |
target_language_code = LANGUAGE_NAME_TO_CODE[target_language]
|
|
|
|
| 291 |
examples=[
|
| 292 |
["assets/sample_input.mp3", "French"],
|
| 293 |
["assets/sample_input.mp3", "Mandarin Chinese"],
|
| 294 |
+
["assets/sample_input_2.mp3", "Hindi"],
|
| 295 |
+
["assets/sample_input_2.mp3", "Spanish"],
|
| 296 |
],
|
| 297 |
inputs=[input_audio_file, target_language],
|
| 298 |
outputs=[output_audio, output_text],
|
|
|
|
| 304 |
examples=[
|
| 305 |
["assets/sample_input.mp3", "French"],
|
| 306 |
["assets/sample_input.mp3", "Mandarin Chinese"],
|
| 307 |
+
["assets/sample_input_2.mp3", "Hindi"],
|
| 308 |
+
["assets/sample_input_2.mp3", "Spanish"],
|
| 309 |
],
|
| 310 |
inputs=[input_audio_file, target_language],
|
| 311 |
outputs=[output_audio, output_text],
|
|
|
|
| 317 |
examples=[
|
| 318 |
["My favorite animal is the elephant.", "English", "French"],
|
| 319 |
["My favorite animal is the elephant.", "English", "Mandarin Chinese"],
|
| 320 |
+
["Meta AI's Seamless M4T model is democratising spoken communication across language barriers",
|
| 321 |
+
"English", "Hindi"],
|
| 322 |
+
["Meta AI's Seamless M4T model is democratising spoken communication across language barriers",
|
| 323 |
+
"English", "Spanish"],
|
| 324 |
],
|
| 325 |
inputs=[input_text, source_language, target_language],
|
| 326 |
outputs=[output_audio, output_text],
|
|
|
|
| 332 |
examples=[
|
| 333 |
["My favorite animal is the elephant.", "English", "French"],
|
| 334 |
["My favorite animal is the elephant.", "English", "Mandarin Chinese"],
|
| 335 |
+
["Meta AI's Seamless M4T model is democratising spoken communication across language barriers",
|
| 336 |
+
"English", "Hindi"],
|
| 337 |
+
["Meta AI's Seamless M4T model is democratising spoken communication across language barriers",
|
| 338 |
+
"English", "Spanish"],
|
| 339 |
],
|
| 340 |
inputs=[input_text, source_language, target_language],
|
| 341 |
outputs=[output_audio, output_text],
|
|
|
|
| 346 |
asr_examples = gr.Examples(
|
| 347 |
examples=[
|
| 348 |
["assets/sample_input.mp3", "English"],
|
| 349 |
+
["assets/sample_input_2.mp3", "English"],
|
| 350 |
],
|
| 351 |
inputs=[input_audio_file, target_language],
|
| 352 |
outputs=[output_audio, output_text],
|
assets/sample_input_2.mp3
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6a505a4641e3f5f0ddec9508832793aa20e63d2545530b66bc04a9bd19a742e6
|
| 3 |
+
size 30624
|