def add_delta(feat,order=2,outFile=None):
'''
Add n order delta to feature.
Share Args:
Null
Parrallel Args:
<feat>: exkaldi feature objects.
<order>: the orders.
<outFile>: output file name.
Return:
exkaldi feature or index table object.
'''
feats,orders,outFiles = check_multiple_resources(feat,order,outFile=outFile)
names = []
for feat,order in zip(feats,orders):
# check feature
declare.is_feature("feat",feat)
# check order
declare.is_positive_int("order",order)
names.append(f"add_delta({feat.name},{order})")
# prepare command pattern and resources
cmdPattern = "add-deltas --delta-order={order} {feat} ark:{outFile}"
resources = {"feat":feats,"order":orders,"outFile":outFiles}
# run
return run_kaldi_commands_parallel(resources,cmdPattern,analyzeResult=True,generateArchive="feat",archiveNames=names)
def compute_cmvn_stats(feat,spk2utt=None,name="cmvn",outFile=None):
'''
Compute CMVN statistics.
Share Args:
Null
Parrallel Args:
<feat>: exkaldi feature object or index table object.
<spk2utt>: spk2utt file or exkaldi ListTable object.
<name>: name of output CMVN object.
<outFile>: output file name.
Return:
exkaldi CMVN statistics or index table object.
'''
feats,spk2utts,names,outFiles = check_multiple_resources(feat,spk2utt,name,outFile=outFile)
for feat,spk2utt in zip(feats,spk2utts):
# verify feature
declare.is_feature("feat",feat)
# verify spk2utt
if spk2utt is not None:
declare.is_potential_list_table("spk2utt",spk2utt)
if spk2utts[0] is None:
cmdPattern = 'compute-cmvn-stats {feat} ark:{outFile}'
resources = {"feat":feats,"outFile":outFiles}
else:
cmdPattern = 'compute-cmvn-stats --spk2utt=ark:{spk2utt} {feat} ark:{outFile}'
resources = {"feat":feats,"spk2utt":spk2utts,"outFile":outFiles}
return run_kaldi_commands_parallel(resources,cmdPattern,analyzeResult=True,generateArchive="cmvn",archiveNames=names)
def use_fmllr(feat,fmllrMat,utt2spk,outFile=None):
'''
Transfrom to fmllr feature.
Share Args:
Null
Parallel Args:
<feat>: exkaldi feature or index table object.
<fmllrMat>: exkaldi fMLLR transform matrix or index table object.
<utt2spk>: file name or ListTable object.
<outFile>: output file name.
Return:
exkaldi feature or index table object.
'''
feats,fmllrMats,utt2spks,outFiles = check_multiple_resources(feat,fmllrMat,utt2spk,outFile=outFile)
names = []
for index,feat,fmllrMat,utt2spk in zip(range(len(outFiles)),feats,fmllrMats,utt2spks):
# verify data
declare.is_feature("feat",feat)
declare.is_fmllr_matrix("fmllrMat",fmllrMat)
# verify utt2spk
declare.is_potential_list_table("utt2spk",utt2spk)
names.append(f"fmllr({feat.name},{fmllrMat.name})")
cmdPattern = 'transform-feats --utt2spk=ark:{utt2spk} {transMat} {feat} ark:{outFile}'
resources = {"feat":feats,"transMat":fmllrMats,"utt2spk":utt2spks,"outFile":outFiles}
return run_kaldi_commands_parallel(resources,cmdPattern,analyzeResult=True,generateArchive="feat",archiveNames=names)
def transform_feat(feat,matFile,outFile=None):
'''
Transform feat by a transform matrix. Typically,LDA,MLLT matrices.
Note that is you want to transform FMLLR,use exkaldi.use_fmllr() function.
Share Args:
Null
Parallel Args:
<feat>: exkaldi feature or index table object.
<matFile>: file name.
<outFile>: output file name.
Return:
exkaldi feature or index table object.
'''
feats,matFiles,outFiles = check_multiple_resources(feat,matFile,outFile=outFile)
names = []
for feat,matFile in zip(feats,matFiles):
declare.is_feature("feat",feat)
declare.is_file("matFile",matFile)
names.append( f"tansform({feat.name})" )
cmdPattern = 'transform-feats {matFile} {feat} ark:{outFile}'
resources = {"feat":feats,"matFile":matFiles,"outFile":outFiles}
return run_kaldi_commands_parallel(resources,cmdPattern,analyzeResult=True,generateArchive="feat",archiveNames=names)
def paste_feature(feats):
'''
Paste feature in feature dimension.
Args:
<feats>: a list of feature objects.
Return:
a new feature object.
'''
declare.kaldi_existed()
assert isinstance(feats,(list,tuple)) and len(feats) > 0
for fe in feats:
declare.is_feature("feats", fe)
allResp = []
pastedName = []
with FileHandleManager() as fhm:
for ot in feats:
if isinstance(ot,BytesFeat):
temp = fhm.create("wb+",suffix=".ark")
ot.sort(by="utt").save(temp)
allResp.append( f"ark:{temp.name}" )
elif isinstance(ot,NumpyFeat):
temp = fhm.create("wb+",suffix=".ark")
ot.sort(by="utt").to_bytes().save(temp)
allResp.append( f"ark:{temp.name}" )
else:
temp = fhm.create("w+",suffix=".scp")
ot.sort(by="utt").save(temp)
allResp.append( f"scp:{temp.name}" )
pastedName.append( ot.name )
allResp = " ".join(allResp)
cmd = f"paste-feats {allResp} ark:-"
out,err,cod = run_shell_command(cmd,stdin="PIPE",stdout="PIPE",stderr="PIPE")
if cod != 0 or out == b'':
raise KaldiProcessError("Failed to paste feature.",err.decode())
else:
pastedName = ",".join(pastedName)
pastedName = f"paste({pastedName})"
# New index table need to be generated later.
return BytesFeat(out,name=pastedName,indexTable=None)
def splice_feature(feat,left,right=None,outFile=None):
'''
Splice left-right N frames to generate new feature.
The dimentions will become original-dim * (1 + left + right)
Share Args:
Null
Parrallel Args:
<feat>: feature or index table object.
<left>: the left N-frames to splice.
<right>: the right N-frames to splice. If None,right = left.
<outFile>; output file name.
Return:
exkaldi feature object or index table object.
'''
feats,lefts,rights,outFiles = check_multiple_resources(feat,left,right,outFile=outFile)
names = []
for index,feat,left,right in zip(range(len(outFiles)),feats,lefts,rights):
# check feature
declare.is_feature("feat",feat)
# check left
declare.is_non_negative_int("left",left)
# check right
if right is None:
assert left != 0,f"At least one of <left> or <right> is valid but got:{left},{right}."
rights[index] = left
else:
declare.is_non_negative_int("right",right)
assert left != 0,"Al least one of <left> or <right> is not 0."
assert not (left == 0 and right == 0),f"At least one of <left> or <right> is valid but got:{left},{right}."
names.append( f"splice({feat.name},{left},{right})" )
# prepare command pattern and resources
cmdPattern = "splice-feats --left-context={left} --right-context={right} {feat} ark:{outFile}"
resources = {"feat":feats,"left":lefts,"right":rights,"outFile":outFiles}
# run
return run_kaldi_commands_parallel(resources,cmdPattern,analyzeResult=True,generateArchive="feat",archiveNames=names)
def use_cmvn(feat,cmvn,utt2spk=None,std=False,outFile=None):
'''
Apply CMVN statistics to feature.
Share Args:
Null
Parrallel Args:
<feat>: exkaldi feature or index table object.
<cmvn>: exkaldi CMVN statistics or index object.
<utt2spk>: file path or ListTable object.
<std>: If true,apply std normalization.
<outFile>: out file name.
Return:
feature or index table object.
'''
feats,cmvns,utt2spks,stds,outFiles = check_multiple_resources(feat,cmvn,utt2spk,std,outFile=outFile)
names = []
for i,feat,cmvn,utt2spk,std in zip(range(len(outFiles)),feats,cmvns,utt2spks,stds):
# verify feature and cmvn
declare.is_feature("feat",feat)
declare.is_cmvn("cmvn",cmvn)
# verify utt2spk
if utt2spk is not None:
declare.is_potential_list_table("utt2spk",utt2spk)
# std
declare.is_bool("std",std)
#stds[i] = "true" if std else "false"
names.append( f"cmvn({feat.name},{cmvn.name})" )
if utt2spks[0] is None:
cmdPattern = 'apply-cmvn --norm-vars={std} {cmvn} {feat} ark:{outFile}'
resources = {"feat":feats,"cmvn":cmvns,"std":stds,"outFile":outFiles}
else:
cmdPattern = 'apply-cmvn --norm-vars={std} --utt2spk=ark:{utt2spk} {cmvn} {feat} ark:{outFile}'
resources = {"feat":feats,"cmvn":cmvns,"utt2spk":utt2spks,"std":stds,"outFile":outFiles}
return run_kaldi_commands_parallel(resources,cmdPattern,analyzeResult=True,generateArchive="feat",archiveNames=names)