def generate_html():
a = Airium()
a('<!DOCTYPE html>')
with a.html():
with a.head():
a.title(_t="Speech Evaluation")
a.meta(name="viewport",
content="width=device-width, initial-scale=1.0")
with a.body():
a.h5(_t="Hello, world!")
return str(a)
def generate_html():
a = Airium()
a('<!DOCTYPE html>')
with a.html():
with a.head():
a.title(_t="TTS Demo Files")
a.meta(name="viewport",
content="width=device-width, initial-scale=1.0")
a.link(
href=
"https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css",
rel="stylesheet",
integrity=
"sha384-eOJMYsd53ii+scO/bJGFsiCZc+5NDVN2yr8+0RDqr0Ql0h+rP48ckxlpbzKgwra6",
crossorigin="anonymous")
with a.body():
with a.div(klass="container pb-5 pt-5"):
a.h1(_t="Emotional TTS Demo Files",
klass="text-center display-1 pt-5 pb-5")
a.h5(
_t="21/04/19 : Reproduced VAW-GAN based emotion converter",
klass="pt-5 pb-3")
a.h5(
_t=
"21/06/01-A: Added phoneme embeddings to the encoder of VAW-GAN",
klass="pt-5 pb-3")
a.h5(
_t="21/06/01-B: Tested CMU-MOSEI with the vanilla VAW-GAN",
klass="pt-5 pb-3")
a.h5(
_t=
"21/06/22 : Tested VAW-GAN with forced alignment on word-level",
klass="pt-5 pb-3")
a.h5(
_t=
"21/07/06 : Tested VAW-GAN with forced alignment on word-level with MFCC Nonspeech Masking",
klass="pt-5 pb-3")
a.h5(
_t=
"21/08/24-A: Tested VAW-GAN with pyworld.harvest() in WORLD",
klass="pt-5 pb-3")
a.h5(
_t=
"21/08/24-B: Tested VAW-GAN with synthesised neutral speech as the training set",
klass="pt-5 pb-3")
for folder, files_by_file_name in get_file_list().items():
a.h3(_t=
f"Samples from {convert_folder_name_to_date(folder)}",
klass="text-center display-6 pt-5")
for original_file_name, files_by_model in files_by_file_name.items(
):
a.h4(_t=original_file_name,
klass="pt-5 pb-5 text-success")
for model, files in files_by_model.items():
if 'neu' == model:
with a.div(
klass="row row-cols-1 row-cols-md-2 g-4"
):
with a.div(klass="col"):
with a.div(klass="card"):
with a.div(
klass=
"card-body text-center"):
a.h5(
_t=
extract_emotion_from_file_name(
files[0]),
klass="card-title")
a.audio(controls=True,
src=os.path.join(
'samples', folder,
files[0]))
else:
if len(files) > 0:
a.h5(_t=f"Samples Generated with {model}",
klass="pt-5 pb-3")
with a.div(
klass=
"row row-cols-1 row-cols-md-2 g-4"
):
for file in files:
with a.div(klass="col"):
with a.div(klass="card"):
with a.div(
klass=
"card-body text-center"
):
a.h5(
_t=
extract_emotion_from_file_name(
file),
klass="card-title")
a.audio(
controls=True,
src=os.path.join(
'samples',
folder, file))
a.script(
src=
"https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js",
integrity=
"sha384-JEW9xMcG8R+pH31jmWH6WWP0WintQrMb4s7ZOdauHnUtxwoG2vI5DkLtS3qm9Ekf",
crossorigin="anonymous")
return str(a)
