montreal_forced_aligner/corpus/acoustic_corpus.py
def combine_feats(self) -> None:
        """
        Combine feature generation results and store relevant information
        """
        split_directory = self.split_directory
        ignore_check = []
        for job in self.jobs:
            feats_path = job.construct_path(split_directory, "feats", "scp")

            with open(feats_path, "r") as inf:
                for line in inf:
                    line = line.strip()
                    if line == "":
                        continue
                    f = line.split(maxsplit=1)
                    if self.utterances[f[0]].ignored:
                        continue
                    self.utterances[f[0]].features = f[1]
        for utterance in self.utterances:
            if utterance.features is None or utterance.duration < 0.13:
                utterance.ignored = True
                ignore_check.append(utterance.name)
        if ignore_check:
            self.log_warning(
                "There were some utterances ignored due to short duration, see the log file for full "
                "details or run `mfa validate` on the corpus."
            )
            self.log_debug(
                f"The following utterances were too short to run alignment: "
                f"{' ,'.join(ignore_check)}"
            )
        self.write_corpus_information()

        Combine feature generation results and store relevant information
        
Combine feature generation results and store relevant information
Combine feature generation results and store relevant information
def combine_feats(self) -> None:
        split_directory = self.split_directory
        ignore_check = []
        for job in self.jobs:
            feats_path = job.construct_path(split_directory, "feats", "scp")
            with open(feats_path, "r") as inf:
                for line in inf:
                    line = line.strip()
                    if line == "":
                        continue
                    f = line.split(maxsplit=1)
                    if self.utterances[f[0]].ignored:
                        continue
                    self.utterances[f[0]].features = f[1]
        for utterance in self.utterances:
            if utterance.features is None or utterance.duration < 0.13:
                utterance.ignored = True
                ignore_check.append(utterance.name)
        if ignore_check:
            self.log_warning(
                "There were some utterances ignored due to short duration, see the log file for full "
                "details or run `mfa validate` on the corpus."
            )
            self.log_debug(
                f"The following utterances were too short to run alignment: "
                f"{' ,'.join(ignore_check)}"
            )
        self.write_corpus_information()
def combine_feats ( self ) -> None : split_directory = self . split_directory ignore_check = [ ] for job in self . jobs : feats_path = job . construct_path ( split_directory , "feats" , "scp" ) with open ( feats_path , "r" ) as inf : for line in inf : line = line . strip ( ) if line == "" : continue f = line . split ( maxsplit = 1 ) if self . utterances [ f [ 0 ] ] . ignored : continue self . utterances [ f [ 0 ] ] . features = f [ 1 ] for utterance in self . utterances : if utterance . features is None or utterance . duration < 0.13 : utterance . ignored = True ignore_check . append ( utterance . name ) if ignore_check : self . log_warning ( "There were some utterances ignored due to short duration, see the log file for full " "details or run `mfa validate` on the corpus." ) self . log_debug ( f"The following utterances were too short to run alignment: " f"{' ,'.join(ignore_check)}" ) self . write_corpus_information ( )
Combine feature generation results and store relevant information
Combine feature generation results and store relevant information
"""
        Combine feature generation results and store relevant information
        """
self