def align_json(ref_txt, json_file, filename=None):
"""
CLI for forced alignment tools
Using a reference txt file and a hypothesis gk json
file, this time-aligns the reference txt file
and outputs an STM file
Input
ref_txt, str - reference text file containing ground truth
json_file, str - hypothesis gk JSON file
filename, str - output STM filename
"""
ref_tokens = preprocess_txt.parse_transcript(ref_txt)
gk_json = preprocess_gk_json.preprocess_transcript(json_file)
segments = align(gk_json, ref_tokens)
if filename is None:
filename = basename(sanitize(strip_extension(ref_txt))) + ".stm"
# fix segment filename and speaker
for seg in segments:
seg.filename = strip_extension(filename)
seg.speaker = strip_extension(filename) + "UnknownSpeaker"
output = time_aligned_text()
output.segments = segments
output.write(filename)
def validate(self):
" validate exemplar object by constraining that the filenames before the extension are the same "
audio_filename = basename(strip_extension(self.audio_file.location))
transcript_filename = basename(
strip_extension(self.transcript_file.location))
# Audio and transcript filename must match
# Audio file must not be empty
# Transcript file must not be empty
valid = (audio_filename == transcript_filename
and os.path.getsize(self.audio_file.location)
and os.path.getsize(self.transcript_file.location))
return valid
def combine_transcripts(transcripts, output_file_name):
# Get one list of segments
out_transcript = reduce(operator.add, transcripts)
out_transcript.location = os.path.join(
strip_extension(output_file_name) + "." + out_transcript.file_extension
)
out_transcript.write(out_transcript.location)
def __init__(self, *args, **kwargs):
"""
Initialize from location and populate list of
SPH, WAV, or MP3 audio files
and STM files into segments
"""
for dictionary in args:
if isinstance(dictionary, dict):
for key in dictionary:
setattr(self, key, dictionary[key])
for key in kwargs:
setattr(self, key, kwargs[key])
# only if not defined above should we search for exemplars
# based on location
if not self.exemplars:
# instantiate exemplars for this object to override
# static class variable
self.exemplars = []
audio_extensions_to_try = ["sph", "wav", "mp3"][::-1]
self.exemplars += [
exemplar({
"audio_file":
audio_file(fl),
"transcript_file":
time_aligned_text(strip_extension(fl) + ".stm"),
}) for audio_extension in audio_extensions_to_try
for fl in (get_files(self.location, audio_extension) if self.
location else [])
if (os.path.exists(strip_extension(fl) + ".stm"))
]
# gather all exemplars from /stm and /sph subdirectories if present
self.exemplars += [
exemplar({
"audio_file":
audio_file(fl),
"transcript_file":
time_aligned_text(self.location + "/stm/" +
basename(strip_extension(fl)) + ".stm"),
}) for audio_extension in audio_extensions_to_try for fl in
(get_files(self.location +
"/sph/", audio_extension) if self.location else [])
if (os.path.exists(self.location + "/stm/" +
basename(strip_extension(fl)) + ".stm"))
]
def validate(self):
"""
Validates exemplar object by constraining that the filenames before the
extension are the same
"""
audio_filename = basename(strip_extension(self.audio_file.location))
transcript_filename = basename(
strip_extension(self.transcript_file.location))
# Audio and transcript filename must match
# Audio file must not be empty
# Transcript file must not be empty
valid = (audio_filename == transcript_filename
and os.path.getsize(self.audio_file.location)
and os.path.getsize(self.transcript_file.location))
# This returns an integer corresponding to the output of the last condition, not a boolean.
# Thats just how `and` works in python
return bool(valid)
def extract_xlsx(filename, target_folder):
"""
For an excel spreadsheet, extract to a text file
"""
working_excel_data_structure = pd.ExcelFile(filename)
raw_name = sanitize(strip_extension(basename(filename)))
with open(''.join([target_folder, '/', raw_name, ".txt"]),
'a+') as output_file:
for sheet in working_excel_data_structure.sheet_names:
dump_sheet(output_file,
working_excel_data_structure.parse(sheet).values)
def prepare_for_training(self, file_name, sample_rate=16000):
"""
Converts to single channel (from channel 1) audio file in SPH file format
"""
if file_name.split(".")[-1] != 'sph':
print("Forcing training data to use SPH file format")
file_name = strip_extension(file_name) + ".sph"
file_name = sanitize_hyphens(file_name)
subprocess.call(["sox {} {} rate {} remix -".format(self.location, file_name, sample_rate)], shell=True)
# return new object
return audio_file(file_name)
def prepare_for_training(self, file_name, sample_rate=16000):
"""
Converts to single channel (from channel 1) audio file in SPH file format
Returns audio_file object on success, else None
"""
if file_name.split(".")[-1] != "sph":
LOGGER.warning(
"Forcing training data to use SPH file format for %s",
file_name)
file_name = strip_extension(file_name) + ".sph"
file_name = sanitize_hyphens(file_name)
# return None if error code given, otherwise return audio_file object
output_file = (audio_file(file_name) if not subprocess.call(
"sox -V1 {} {} rate {} remix -".format(self.location, file_name,
sample_rate),
shell=True,
) else None)
return output_file