head_st.append(k + " " + h)
for e, k in enumerate(head_st):
df[k] = Features[:, e]
else:
df = {}
for e, k in enumerate(self.head):
df[k] = Features[:, e]
df["id"] = ids
return pd.DataFrame(df)
elif fmt == "torch":
return torch.from_numpy(Features)
elif fmt == "kaldi":
if static:
raise ValueError(
"Kaldi is only supported for dynamic features")
else:
dictX = get_dict(Features, ids)
save_dict_kaldimat(dictX, kaldi_file)
if __name__ == "__main__":
if len(sys.argv) != 6:
print(
"python glottal.py <file_or_folder_audio> <file_features> <static (true, false)> <plots (true, false)> <format (csv, txt, npy, kaldi, torch)>"
)
sys.exit()
glottal = Glottal()
script_manager(sys.argv, glottal)
df[k] = Features[:, e]
else:
df = {}
for e, k in enumerate(self.head):
df[k] = Features[:, e]
df["id"] = ids
return pd.DataFrame(df)
elif fmt == "torch":
return torch.from_numpy(Features)
elif fmt == "kaldi":
if static:
raise ValueError(
"Kaldi is only supported for dynamic features")
else:
dictX = get_dict(Features, ids)
save_dict_kaldimat(dictX, kaldi_file)
else:
raise ValueError(fmt + " is not supported")
if __name__ == "__main__":
if len(sys.argv) != 6:
print(
"python phonation.py <file_or_folder_audio> <file_features> <static (true, false)> <plots (true, false)> <format (csv, txt, npy, kaldi, torch)>"
)
sys.exit()
phonation = Phonation()
script_manager(sys.argv, phonation)
df = {}
for e, k in enumerate(self.head_st):
df[k] = Features[:, e]
else:
df = {}
for e, k in enumerate(self.head_dyn):
df[k] = Features[:, e]
df["id"] = ids
return pd.DataFrame(df)
if fmt == "torch":
return torch.from_numpy(Features)
if fmt == "kaldi":
if static:
raise ValueError(
"Kaldi is only supported for dynamic features")
dictX = get_dict(Features, ids)
save_dict_kaldimat(dictX, kaldi_file)
else:
raise ValueError(fmt + " is not supported")
if __name__ == "__main__":
if len(sys.argv) != 6:
print(
"python prosody.py <file_or_folder_audio> <file_features> <static (true, false)> <plots (true, false)> <format (csv, txt, npy, kaldi, torch)>"
)
sys.exit()
prosody = Prosody()
script_manager(sys.argv, prosody)
for e, k in enumerate(self.head_st):
df[k] = Features[:, e]
else:
df = {}
for e, k in enumerate(self.head_dyn):
df[k] = Features[:, e]
df["id"] = ids
return pd.DataFrame(df)
if fmt == "torch":
return torch.from_numpy(Features)
if fmt == "kaldi":
if static:
raise ValueError(
"Kaldi is only supported for dynamic features")
dictX = get_dict(Features, ids)
save_dict_kaldimat(dictX, kaldi_file)
else:
raise ValueError(fmt + " is not supported")
if __name__ == "__main__":
if len(sys.argv) != 6:
print(
"python phonological.py <file_or_folder_audio> <file_features> <static (true, false)> <plots (true, false)> <format (csv, txt, npy, kaldi, torch)>"
)
sys.exit()
phonological = Phonological()
script_manager(sys.argv, phonological)
if fmt in("dataframe","csv"):
if static:
df={}
for e, k in enumerate(self.head_st):
df[k]=Features[:,e]
else:
df={}
for e, k in enumerate(self.head_dyn):
df[k]=Features[:,e]
df["id"]=ids
return pd.DataFrame(df)
if fmt=="torch":
return torch.from_numpy(Features)
if fmt=="kaldi":
if static:
raise ValueError("Kaldi is only supported for dynamic features")
dictX=get_dict(Features, ids)
save_dict_kaldimat(dictX, kaldi_file)
else:
raise ValueError(fmt+" is not supported")
if __name__=="__main__":
if len(sys.argv)!=7:
print("python replearning.py <file_or_folder_audio> <file_features> <static (true, false)> <plots (true, false)> <format (csv, txt, npy, kaldi, torch)> <model (CAE,RAE)>")
sys.exit()
replearning=RepLearning(sys.argv[-1])
script_manager(sys.argv, replearning)
for h in self.head:
head_st.append(k + " " + h)
for e, k in enumerate(head_st):
df[k] = Features[:, e]
else:
df = {}
for e, k in enumerate(self.head_dyn):
df[k] = Features[:, e]
df["id"] = ids
return pd.DataFrame(df)
if fmt == "torch":
return torch.from_numpy(Features)
if fmt == "kaldi":
if static:
raise ValueError(
"Kaldi is only supported for dynamic features")
dictX = get_dict(Features, ids)
save_dict_kaldimat(dictX, kaldi_file)
if __name__ == "__main__":
if len(sys.argv) != 6:
print(
"python articulation.py <file_or_folder_audio> <file_features> <static (true, false)> <plots (true, false)> <format (csv, txt, npy, kaldi, torch)>"
)
sys.exit()
articulation = Articulation()
script_manager(sys.argv, articulation)
