def word_to_phone_mlf(model, dict, word_mlf, phone_mlf, mono_list):
"""
Convert the word-level mlf to a phone level mlf with HLEd
"""
if not os.path.isfile(word_mlf):
util.log_write(model.logfh, 'No word MLF file here [%s]' % word_mlf)
util.exit(model.log)
if not os.path.isfile(dict):
util.log_write(model.logfh, 'No dict file here [%s]' % dict)
util.exit(model.log)
## Create mkphones0.led
led_file = '%s/mkphones0.led' % model.exp
fh = open(led_file, 'w')
fh.write('EX\nIS sil sil\n')
fh.close()
## Convert the word level MLF into a phone MLF
cmd_log = '%s/hhed_word_to_phone.log' % model.exp
cmd = 'HLEd -A -T 1 -l "*"'
cmd += ' -d %s' % dict
cmd += ' -i %s' % phone_mlf
cmd += ' %s %s > %s' % (led_file, word_mlf, cmd_log)
os.system(cmd)
## Create list of phones (appearing in the phone MLF)
monophones = set()
for line in open(phone_mlf):
phone = line.strip()
if phone.isalpha(): monophones.add(phone)
monophones = list(monophones)
monophones.sort()
fh = open(mono_list, 'w')
for phone in monophones:
fh.write('%s\n' % phone)
fh.close()
return len(monophones)
def word_to_phone_mlf(model, dict, word_mlf, phone_mlf, mono_list):
"""
Convert the word-level mlf to a phone level mlf with HLEd
"""
if not os.path.isfile(word_mlf):
util.log_write(model.logfh, 'No word MLF file here [%s]' %word_mlf)
util.exit(model.log)
if not os.path.isfile(dict):
util.log_write(model.logfh, 'No dict file here [%s]' %dict)
util.exit(model.log)
## Create mkphones0.led
led_file = '%s/mkphones0.led' %model.exp
fh = open(led_file, 'w')
fh.write('EX\nIS sil sil\n')
fh.close()
## Convert the word level MLF into a phone MLF
cmd_log = '%s/hhed_word_to_phone.log' %model.exp
cmd = 'HLEd -A -T 1 -l "*"'
cmd += ' -d %s' %dict
cmd += ' -i %s' %phone_mlf
cmd += ' %s %s > %s' %(led_file, word_mlf, cmd_log)
os.system(cmd)
## Create list of phones (appearing in the phone MLF)
monophones = set()
for line in open(phone_mlf):
phone = line.strip()
if phone.isalpha(): monophones.add(phone)
monophones = list(monophones)
monophones.sort()
fh = open(mono_list, 'w')
for phone in monophones: fh.write('%s\n' %phone)
fh.close()
return len(monophones)
def make_mlf_from_transcripts(model, orig_dict, setup, data_path, word_mlf, mfc_list, skip_oov=True):
"""
An MLF is an HTK-formatted transcription file. This is created
from the word-level transcripts in setup.
"""
replace_escaped_words = True
## Load the dictionary words
dict_words = set([entry.split()[0].upper() for entry in open(orig_dict).read().splitlines()
if not entry.startswith('#') and len(entry.strip()) > 0])
words = set()
if setup.endswith('gz'): setup_reader = lambda x: gzip.open(x)
else: setup_reader = lambda x: open(x)
## Create MLF-format entries for each utterance
mfcs = []
mlf = ['#!MLF!#']
count = 0
for line in setup_reader(setup):
skip = False
items = line.strip().split()
wav = items[0]
mfc = coding.get_mfc_name_from_wav(wav, data_path)
curr = ['"*/%s.lab"' %os.path.basename(wav).split('.')[0]]
trans = map(str.upper, items[2:])
for word in trans:
if replace_escaped_words and '\\' in word:
new_word = re.sub(r'\\[^A-Za-z0-9]*', r'', word)
if new_word in dict_words: word = new_word
if word not in dict_words:
## Don't include bracketed words or periods in the labels
if word.startswith('[') and word.endswith(']'): continue
if word == '.': continue
if model.verbose > 0: util.log_write(model.logfh, 'not in dictionary [%s]' %word)
## Remove the utterance if there are other non-dictionary words
if skip_oov: skip = True
if word[0].isdigit(): word = '_' + word
curr.append(word)
## Check for empty transcriptions
if len(curr) <= 1: skip = True
curr.append('.')
if not skip:
mlf.extend(curr)
for word in curr:
words.add(word)
mfcs.append(mfc)
count += 1
## Write the MLF
fh = open(word_mlf, 'w')
fh.write('\n'.join(mlf) + '\n')
fh.close()
## Create a new MFC list file
fh = open(mfc_list, 'w')
for mfc in mfcs: fh.write('%s\n' %mfc)
fh.close()
return count, words
def build_lm_from_mlf(model, word_mlf, dictionary, vocab, lm_dir, lm, lm_order, target_ppl_ratio=None):
"""
Build a language model using SRILM
Use the transcripts in the word mlf
Output to lm
Output intermediate files in lm_dir
Return perplexity on the training text
"""
dict = set([entry.split()[0].upper() for entry in open(dictionary).read().splitlines()
if not entry.startswith('#') and len(entry.strip()) > 0])
## Prepare to build an LM by creating a file with one sentence per line
text_file = '%s/training.txt' %lm_dir
text, curr = [], []
## Extract a vocab from the MLF
cmd = 'cat %s | grep ".lab" -v | grep "MLF" -v | sort | uniq' %word_mlf
mlf_vocab = set(os.popen(cmd).read().splitlines())
mlf_dict_vocab = list(mlf_vocab.intersection(dict))
mlf_dict_vocab.sort()
fh = open(vocab, 'w')
for word in mlf_dict_vocab: fh.write(word + '\n')
fh.close()
for line in open(word_mlf):
line = line.strip()
if line.startswith('#!MLF'): continue
if line.startswith('"') and '.lab' in line: continue
if line == '.':
text.append(' '.join(curr))
curr = []
continue
curr.append(line)
fh = open(text_file, 'w')
fh.write('\n'.join(text))
fh.close()
## Build a language model
cutoff, cutoff_min, cutoff_max = 5, 1, 50
iters, prev_cutoff = 0, 0
cmd = 'ngram-count -vocab %s -order %d -text %s -lm %s' %(vocab, lm_order, text_file, lm)
util.run(cmd, lm_dir)
cmd = 'ngram -order %d -lm %s -ppl %s -debug 0' %(lm_order, lm, text_file)
res = util.run(cmd, lm_dir)
ppl = float(os.popen('grep zeroprobs %s' %res).read().split()[5])
if not target_ppl_ratio: return ppl
util.log_write(model.logfh, ' cutoff [%d] gives ppl [%1.2f]' %(1, ppl))
target_ppl = ppl * target_ppl_ratio
while True:
iters += 1
params = '-gt%dmin %d' %(lm_order, cutoff)
cmd = 'ngram-count -vocab %s -order %d -text %s -lm %s %s' %(vocab, lm_order, text_file, lm, params)
util.run(cmd, lm_dir)
cmd = 'ngram -order %d -lm %s -ppl %s -debug 0' %(lm_order, lm, text_file)
res = util.run(cmd, lm_dir)
ppl = float(os.popen('grep zeroprobs %s' %res).read().split()[5])
if not target_ppl or abs(ppl - target_ppl) < 1: break
if cutoff == prev_cutoff or iters > 10: break
prev_cutoff = cutoff
util.log_write(model.logfh, ' cutoff [%d] gives ppl [%1.2f]' %(cutoff, ppl))
if ppl < target_ppl:
cutoff_min = cutoff
cutoff = (cutoff + cutoff_max) / 2
else:
cutoff_max = cutoff
cutoff = (cutoff + cutoff_min) / 2
## Return perplexity on the training data
return ppl
def decode_to_lattices(model, output_dir, model_dir, mfc_list, lm, dict,
model_list, gold_mlf):
sys.stderr.write('Decoding to lattices\n')
output_mlf = '%s/train_recog.mlf' % output_dir
results_log = '%s/results.log' % output_dir
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' % output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 150.0
word_end_beam = 125.0
max_model = 10000
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode(input, output):
cmd = 'HDecode -A -D -V -T 9 -o M -z lat -C %s' % hdecode_config
cmd += ' -H %s/MMF' % model_dir
cmd += ' -k %d' % block_size
cmd += ' -t %f 100.0' % beam
cmd += ' -v %f 115.0' % word_end_beam
cmd += ' -u %d' % max_model
cmd += ' -s %f' % lm_scale
cmd += ' -p %f' % word_insertion_penalty
cmd += ' -w %s' % lm
cmd += ' -S %s' % input
cmd += ' -l %s/' % output
cmd += ' %s %s' % (dict, model_list)
if model.verbose > 0:
cmd += ' >%s/%s.log' % (output_dir, os.path.basename(input))
return cmd
## Split up MFC list
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
output = '%s/%s' % (output_dir, split_mfc.get_key(input))
if not os.path.isdir(output): os.makedirs(output)
cmds.append(hdecode(input, output))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode.commands' % output_dir
fh = open(cmds_file, 'w')
for cmd in cmds:
fh.write('%s\n' % cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' % output_dir
os.system('cp %s %s' % (mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [
os.path.basename(f).split('.')[0]
for f in util.get_files(output_dir, r'.*\.lat')
]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1:
util.log_write(model.logfh, 'removed bad lat [%s]' % id)
bad_count += 1
else:
fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' % bad_count)
## Create an MLF from the recognition output
outputs = util.get_files(output_dir, r'.*\.rec')
os.popen('rm -f %s' % output_mlf)
fh = open(output_mlf, 'w')
fh.write('#!MLF!#\n')
for output in outputs:
fh.write('"%s"\n' % output)
for line in open(output):
if '<s>' in line or '</s>' in line: continue
fh.write(line)
fh.write('.\n')
fh.close()
## Evaluate
cmd = 'HResults -h -n -A -T 1'
cmd += ' -I %s' % gold_mlf
cmd += ' %s %s > %s' % (model_list, output_mlf, results_log)
os.system(cmd)
print os.popen('cat ' + results_log).read()
def phonemark_lattices(model, lattice_dir, output_dir, model_dir, mfc_list, lm,
dict, model_list):
sys.stderr.write('Phonemarking lattices\n')
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' % output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 200.0
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode_mod(input, path):
input_dir = '%s/%s/' % (lattice_dir, path)
if not os.path.isdir(input_dir):
input_dir = '%s/%s/' % (lattice_dir, path.replace('_', ''))
cmd = 'HDecode.mod -A -D -V -T 9 -q tvaldm -z lat -X lat -C %s' % hdecode_config
cmd += ' -H %s/MMF' % model_dir
cmd += ' -k %d' % block_size
cmd += ' -t %f' % beam
cmd += ' -s %f' % lm_scale
cmd += ' -p %f' % word_insertion_penalty
cmd += ' -w' # %s' %lm
cmd += ' -S %s' % input
cmd += ' -l %s/%s/' % (output_dir, path)
cmd += ' -L %s' % input_dir
cmd += ' %s %s' % (dict, model_list)
if model.verbose > 0:
cmd += ' >%s/%s.log' % (output_dir, os.path.basename(input))
return cmd
## Split up MFC list with unix split
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
key = split_mfc.get_key(input)
new_output = '%s/%s' % (output_dir, key)
if not os.path.isdir(new_output): os.makedirs(new_output)
cmds.append(hdecode_mod(input, key))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode_mod.commands' % output_dir
fh = open(cmds_file, 'w')
for cmd in cmds:
fh.write('%s\n' % cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' % output_dir
os.system('cp %s %s' % (mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [
os.path.basename(f).split('.')[0]
for f in util.get_files(output_dir, r'.*\.lat')
]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1:
util.log_write(model.logfh, 'removed bad lat [%s]' % id)
bad_count += 1
else:
fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' % bad_count)
def tie_states_search(model, output_dir, model_dir, mono_list, tri_list, tied_list):
"""
Tie HMM states using decision tree clustering
"""
util.create_new_dir(output_dir)
tree_hed = '%s/tree.hed' %output_dir
tree_output = '%s/trees' %output_dir
hhed_log = '%s/hhed_cluster.log' %output_dir
all_tri_list = '%s/all_tri.list' %model.exp
## Decision tree parameters
ro = model.dt_ro
tb = model.dt_tb
tb_min = 100.0
tb_max = 10000.0
## Create the full list of possible triphones
phones = open(mono_list).read().splitlines()
non_sp_phones = [p for p in phones if p not in ['sp', 'sil']]
fh = open(all_tri_list, 'w')
fh.write('sp\n')
fh.write('sil\n')
for p1 in non_sp_phones:
fh.write('sil-%s+sil\n' %p1)
for p2 in non_sp_phones:
fh.write('sil-%s+%s\n' %(p1, p2))
fh.write('%s-%s+sil\n' %(p2, p1))
for p3 in non_sp_phones:
fh.write('%s-%s+%s\n' %(p2, p1, p3))
fh.close()
## Search over tb arguments to get the right number states
num_states = 0
attempts = 0
prev_tb = 0
while True:
os.system('rm -f %s %s %s' %(tree_hed, tree_output, hhed_log))
## Set up decision tree clustering
fh = open(tree_hed, 'w')
fh.write('RO %d %s/stats\n' %(ro, model_dir))
fh.write('TR 0\n')
fh.write('%s\n' %open(model.tree_questions).read())
fh.write('TR 12\n')
for p in non_sp_phones:
for s in range(1, model.states+1)[1:-1]:
fh.write('TB %d "ST_%s_%d_" {(%s,*-%s+*,%s+*,*-%s).state[%d]}\n' %(tb,p,s,p,p,p,p,s))
fh.write('TR 1\n')
fh.write('AU "%s"\n' %all_tri_list)
fh.write('CO "%s"\n' %tied_list)
fh.write('ST "%s"\n' %tree_output)
fh.close()
## Use HHEd to cluster
cmd = 'HHEd -A -T 1 -H %s/MMF' %model_dir
cmd += ' -M %s' %output_dir
cmd += ' %s %s > %s' %(tree_hed, tri_list, hhed_log)
if model.local == 1: os.system(cmd)
else: util.run(cmd, output_dir)
num_states = int(os.popen('grep -c "<MEAN>" %s/MMF' %output_dir).read().strip())
if abs(float(num_states - model.triphone_states)/model.triphone_states) <= 0.01:
util.log_write(model.logfh, ' current states [%d] tb [%1.2f]' %(num_states, tb))
break
if abs(prev_tb - tb) <= 0.01:
util.log_write(model.logfh, ' Could not converge. Stopping. Current states [%d] tb [%1.2f]' %(num_states,tb))
break
attempts += 1
prev_tb = tb
if num_states < model.triphone_states:
tb = (tb_min + tb) / 2
tb_max = prev_tb
else:
tb = (tb_max + tb) / 2
tb_min = prev_tb
util.log_write(model.logfh, ' [%d] goal [%d] current states [%d] tb [%1.2f] -> [%1.2f] [%1.1f %1.1f]' %(attempts, model.triphone_states, num_states, prev_tb, tb, tb_min, tb_max))
if attempts > 50:
util.log_write(model.logfh, ' Goal not reached after 50 tries. Exiting.')
sys.exit()
return output_dir
def align(model, root_dir, mfc_list, model_dir, word_mlf, new_mlf, model_list, dict, align_config):
"""
Create a new alignment based on a model and the word alignment with HVite
"""
output_dir = '%s/Align' %root_dir
util.create_new_dir(output_dir)
utts_per_split = max(100, (1 + (model.setup_length / 200)))
## Copy old mfc list
os.system('cp %s %s/mfc_old.list' %(mfc_list, output_dir))
## HVite parameters
prune_thresh = 250
def hvite(input, output):
#-o SWT
cmd = 'HVite -D -A -T 1 -b silence -a -m -y lab '
cmd += '-t %d' %prune_thresh
cmd += ' -C %s' %align_config
cmd += ' -H %s/MMF' %model_dir
cmd += ' -i %s' %output
cmd += ' -I %s' %word_mlf
cmd += ' -S %s' %input
cmd += ' %s %s' %(dict, model_list)
cmd += ' >> %s.hvite.log' %output
return cmd
## Split up MFC list with unix split
cmd = 'split -a 4 -d -l %d %s %s/%s' %(utts_per_split, mfc_list, output_dir, 'mfc.list.')
os.system(cmd)
## Create the HVite commands
cmds = []
outputs = []
inputs = os.popen('ls %s/mfc.list.*' %output_dir).read().splitlines()
for input in inputs:
output = input.replace('mfc.list', 'align.output')
outputs.append(output)
cmds.append(hvite(input, output))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hvite.commands' %output_dir
fh = open(cmds_file, 'w')
for cmd in cmds: fh.write('%s\n' %cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Merge and fix silences
## TODO: -s file_list
merge_sil = '%s/merge_sp_sil.led' %output_dir
fh = open(merge_sil, 'w')
fh.write('ME sil sp sil\n')
fh.write('ME sil sil sil\n')
fh.write('ME sp sil sil\n')
fh.close()
cmd = 'HLEd -D -A -T 1 -i %s %s %s >> %s/hled.log' %(new_mlf, merge_sil, ' '.join(outputs), output_dir)
if model.local == 1: os.system(cmd)
else: util.run(cmd, output_dir)
## Prune failed alignments from the mfc list
bad_count = 0
mlf_labels = os.popen('grep "\.lab" %s' %new_mlf).read().splitlines()
mlf_labels = set([os.path.basename(s).split('.')[0] for s in mlf_labels])
mfc_labels = open(mfc_list).read().splitlines()
fh = open(mfc_list, 'w')
for mfc in mfc_labels:
id = os.path.basename(mfc).split('.')[0]
## Check for missing transcriptions
if id not in mlf_labels:
if model.verbose > 0: util.log_write(model.logfh, 'removed bad alignment [%s]' %id)
bad_count += 1
else: fh.write(mfc + '\n')
fh.close()
util.log_write(model.logfh, 'removed alignments [%d]' %bad_count)
## Clean up
os.system('rm -f %s/mfc.list.* %s/align.output.*' %(output_dir, output_dir))
return output_dir
def tie_states_search(model, output_dir, model_dir, mono_list, tri_list,
tied_list):
"""
Tie HMM states using decision tree clustering
"""
util.create_new_dir(output_dir)
tree_hed = '%s/tree.hed' % output_dir
tree_output = '%s/trees' % output_dir
hhed_log = '%s/hhed_cluster.log' % output_dir
all_tri_list = '%s/all_tri.list' % model.exp
## Decision tree parameters
ro = model.dt_ro
tb = model.dt_tb
tb_min = 100.0
tb_max = 10000.0
## Create the full list of possible triphones
phones = open(mono_list).read().splitlines()
non_sp_phones = [p for p in phones if p not in ['sp', 'sil']]
fh = open(all_tri_list, 'w')
fh.write('sp\n')
fh.write('sil\n')
for p1 in non_sp_phones:
fh.write('sil-%s+sil\n' % p1)
for p2 in non_sp_phones:
fh.write('sil-%s+%s\n' % (p1, p2))
fh.write('%s-%s+sil\n' % (p2, p1))
for p3 in non_sp_phones:
fh.write('%s-%s+%s\n' % (p2, p1, p3))
fh.close()
## Search over tb arguments to get the right number states
num_states = 0
attempts = 0
prev_tb = 0
while True:
os.system('rm -f %s %s %s' % (tree_hed, tree_output, hhed_log))
## Set up decision tree clustering
fh = open(tree_hed, 'w')
fh.write('RO %d %s/stats\n' % (ro, model_dir))
fh.write('TR 0\n')
fh.write('%s\n' % open(model.tree_questions).read())
fh.write('TR 12\n')
for p in non_sp_phones:
for s in range(1, model.states + 1)[1:-1]:
fh.write(
'TB %d "ST_%s_%d_" {(%s,*-%s+*,%s+*,*-%s).state[%d]}\n' %
(tb, p, s, p, p, p, p, s))
fh.write('TR 1\n')
fh.write('AU "%s"\n' % all_tri_list)
fh.write('CO "%s"\n' % tied_list)
fh.write('ST "%s"\n' % tree_output)
fh.close()
## Use HHEd to cluster
cmd = 'HHEd -A -T 1 -H %s/MMF' % model_dir
cmd += ' -M %s' % output_dir
cmd += ' %s %s > %s' % (tree_hed, tri_list, hhed_log)
if model.local == 1: os.system(cmd)
else: util.run(cmd, output_dir)
num_states = int(
os.popen('grep -c "<MEAN>" %s/MMF' % output_dir).read().strip())
if abs(
float(num_states - model.triphone_states) /
model.triphone_states) <= 0.01:
util.log_write(
model.logfh,
' current states [%d] tb [%1.2f]' % (num_states, tb))
break
if abs(prev_tb - tb) <= 0.01:
util.log_write(
model.logfh,
' Could not converge. Stopping. Current states [%d] tb [%1.2f]'
% (num_states, tb))
break
attempts += 1
prev_tb = tb
if num_states < model.triphone_states:
tb = (tb_min + tb) / 2
tb_max = prev_tb
else:
tb = (tb_max + tb) / 2
tb_min = prev_tb
util.log_write(
model.logfh,
' [%d] goal [%d] current states [%d] tb [%1.2f] -> [%1.2f] [%1.1f %1.1f]'
% (attempts, model.triphone_states, num_states, prev_tb, tb,
tb_min, tb_max))
if attempts > 50:
util.log_write(model.logfh,
' Goal not reached after 50 tries. Exiting.')
sys.exit()
return output_dir
def align(model, root_dir, mfc_list, model_dir, word_mlf, new_mlf, model_list,
dict, align_config):
"""
Create a new alignment based on a model and the word alignment with HVite
"""
output_dir = '%s/Align' % root_dir
util.create_new_dir(output_dir)
utts_per_split = max(100, (1 + (model.setup_length / 200)))
## Copy old mfc list
os.system('cp %s %s/mfc_old.list' % (mfc_list, output_dir))
## HVite parameters
prune_thresh = 250
def hvite(input, output):
#-o SWT
cmd = 'HVite -D -A -T 1 -b silence -a -m -y lab '
cmd += '-t %d' % prune_thresh
cmd += ' -C %s' % align_config
cmd += ' -H %s/MMF' % model_dir
cmd += ' -i %s' % output
cmd += ' -I %s' % word_mlf
cmd += ' -S %s' % input
cmd += ' %s %s' % (dict, model_list)
cmd += ' >> %s.hvite.log' % output
return cmd
## Split up MFC list with unix split
cmd = 'split -a 4 -d -l %d %s %s/%s' % (utts_per_split, mfc_list,
output_dir, 'mfc.list.')
os.system(cmd)
## Create the HVite commands
cmds = []
outputs = []
inputs = os.popen('ls %s/mfc.list.*' % output_dir).read().splitlines()
for input in inputs:
output = input.replace('mfc.list', 'align.output')
outputs.append(output)
cmds.append(hvite(input, output))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hvite.commands' % output_dir
fh = open(cmds_file, 'w')
for cmd in cmds:
fh.write('%s\n' % cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Merge and fix silences
## TODO: -s file_list
merge_sil = '%s/merge_sp_sil.led' % output_dir
fh = open(merge_sil, 'w')
fh.write('ME sil sp sil\n')
fh.write('ME sil sil sil\n')
fh.write('ME sp sil sil\n')
fh.close()
cmd = 'HLEd -D -A -T 1 -i %s %s %s >> %s/hled.log' % (
new_mlf, merge_sil, ' '.join(outputs), output_dir)
if model.local == 1: os.system(cmd)
else: util.run(cmd, output_dir)
## Prune failed alignments from the mfc list
bad_count = 0
mlf_labels = os.popen('grep "\.lab" %s' % new_mlf).read().splitlines()
mlf_labels = set([os.path.basename(s).split('.')[0] for s in mlf_labels])
mfc_labels = open(mfc_list).read().splitlines()
fh = open(mfc_list, 'w')
for mfc in mfc_labels:
id = os.path.basename(mfc).split('.')[0]
## Check for missing transcriptions
if id not in mlf_labels:
if model.verbose > 0:
util.log_write(model.logfh, 'removed bad alignment [%s]' % id)
bad_count += 1
else:
fh.write(mfc + '\n')
fh.close()
util.log_write(model.logfh, 'removed alignments [%d]' % bad_count)
## Clean up
os.system('rm -f %s/mfc.list.* %s/align.output.*' %
(output_dir, output_dir))
return output_dir
def decode_to_lattices(model, output_dir, model_dir, mfc_list, lm, dict, model_list, gold_mlf):
sys.stderr.write('Decoding to lattices\n')
output_mlf = '%s/train_recog.mlf' %output_dir
results_log = '%s/results.log' %output_dir
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' %output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 150.0
word_end_beam = 125.0
max_model = 10000
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode(input, output):
cmd = 'HDecode -A -D -V -T 9 -o M -z lat -C %s' %hdecode_config
cmd += ' -H %s/MMF' %model_dir
cmd += ' -k %d' %block_size
cmd += ' -t %f 100.0' %beam
cmd += ' -v %f 115.0' %word_end_beam
cmd += ' -u %d' %max_model
cmd += ' -s %f' %lm_scale
cmd += ' -p %f' %word_insertion_penalty
cmd += ' -w %s' %lm
cmd += ' -S %s' %input
cmd += ' -l %s/' %output
cmd += ' %s %s' %(dict, model_list)
if model.verbose > 0: cmd += ' >%s/%s.log' %(output_dir, os.path.basename(input))
return cmd
## Split up MFC list
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
output = '%s/%s' %(output_dir, split_mfc.get_key(input))
if not os.path.isdir(output): os.makedirs(output)
cmds.append(hdecode(input, output))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode.commands' %output_dir
fh = open(cmds_file, 'w')
for cmd in cmds: fh.write('%s\n' %cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' %output_dir
os.system('cp %s %s' %(mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [os.path.basename(f).split('.')[0] for f in util.get_files(output_dir, r'.*\.lat')]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1: util.log_write(model.logfh, 'removed bad lat [%s]' %id)
bad_count += 1
else: fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' %bad_count)
## Create an MLF from the recognition output
outputs = util.get_files(output_dir, r'.*\.rec')
os.popen('rm -f %s' %output_mlf)
fh = open(output_mlf, 'w')
fh.write('#!MLF!#\n')
for output in outputs:
fh.write('"%s"\n' %output)
for line in open(output):
if '<s>' in line or '</s>' in line: continue
fh.write(line)
fh.write('.\n')
fh.close()
## Evaluate
cmd = 'HResults -h -n -A -T 1'
cmd += ' -I %s' %gold_mlf
cmd += ' %s %s > %s' %(model_list, output_mlf, results_log)
os.system(cmd)
print os.popen('cat ' + results_log).read()
def phonemark_lattices(model, lattice_dir, output_dir, model_dir, mfc_list, lm, dict, model_list):
sys.stderr.write('Phonemarking lattices\n')
## Create a config file to use with HDecode
hdecode_config = '%s/hdecode.config' %output_dir
fh = open(hdecode_config, 'w')
#fh.write('HLANGMODFILTER = "gunzip -c $.gz"\n')
fh.write('HNETFILTER = "gunzip -c < $.gz"\n')
fh.write('HNETOFILTER = "gzip -c > $.gz"\n')
fh.write('RAWMITFORMAT = T\n')
fh.write('HPARM: TARGETKIND = MFCC_0_D_A_Z\n')
fh.write('GCFREQ = 50\n')
fh.write('HLAT:TRACE = 19\n')
fh.write('HLVNET:TRACE = 1\n')
fh.write('HLVREC:TRACE = 1\n')
fh.write('HLVLM:TRACE = 1\n')
fh.write('LATPRUNEBEAM = 500.0\n')
fh.write('MAXLMLA = 3.0\n')
fh.write('BUILDLATSENTEND = T\n')
fh.write('FORCELATOUT = F\n')
fh.write('STARTWORD = <s>\n')
fh.write('ENDWORD = </s>\n')
fh.close()
## HDecode parameters
utts_per_split = 100
block_size = 5
beam = 200.0
lm_scale = 15.0
word_insertion_penalty = 0.0
def hdecode_mod(input, path):
input_dir = '%s/%s/' %(lattice_dir, path)
if not os.path.isdir(input_dir):
input_dir = '%s/%s/' %(lattice_dir, path.replace('_', ''))
cmd = 'HDecode.mod -A -D -V -T 9 -q tvaldm -z lat -X lat -C %s' %hdecode_config
cmd += ' -H %s/MMF' %model_dir
cmd += ' -k %d' %block_size
cmd += ' -t %f' %beam
cmd += ' -s %f' %lm_scale
cmd += ' -p %f' %word_insertion_penalty
cmd += ' -w' # %s' %lm
cmd += ' -S %s' %input
cmd += ' -l %s/%s/' %(output_dir, path)
cmd += ' -L %s' %input_dir
cmd += ' %s %s' %(dict, model_list)
if model.verbose > 0: cmd += ' >%s/%s.log' %(output_dir, os.path.basename(input))
return cmd
## Split up MFC list with unix split
split_mfc = SplitList(output_dir, mfc_list, by_path=True)
## Create the HDecode commands
cmds = []
inputs = split_mfc.get_files()
for input in inputs:
key = split_mfc.get_key(input)
new_output = '%s/%s' %(output_dir, key)
if not os.path.isdir(new_output): os.makedirs(new_output)
cmds.append(hdecode_mod(input, key))
if model.local == 1:
for cmd in cmds:
print cmd
print os.popen(cmd).read()
else:
cmds_file = '%s/hdecode_mod.commands' %output_dir
fh = open(cmds_file, 'w')
for cmd in cmds: fh.write('%s\n' %cmd)
fh.close()
util.run_parallel(cmds_file, model.jobs, output_dir)
## Copy old mfc list
old_mfc_list = '%s/mfc_old.list' %output_dir
os.system('cp %s %s' %(mfc_list, old_mfc_list))
## Prune bad lats from the mfc list
lat_ids = [os.path.basename(f).split('.')[0] for f in util.get_files(output_dir, r'.*\.lat')]
bad_count = 0
fh = open(mfc_list, 'w')
for mfc in open(old_mfc_list):
id = os.path.basename(mfc.strip()).split('.')[0]
## Check for missing transcriptions
if id not in lat_ids:
if model.verbose > 1: util.log_write(model.logfh, 'removed bad lat [%s]' %id)
bad_count += 1
else: fh.write(mfc)
fh.close()
util.log_write(model.logfh, 'removed bad lats [%d]' %bad_count)
