montreal_forced_aligner/language_modeling/trainer.py
def train(self) -> None:
        """Convert the arpa model to MFA format"""
        self.log_info("Parsing large ngram model...")

        with open(
            os.path.join(self.working_log_directory, "read.log"), "w", encoding="utf8"
        ) as log_file:
            subprocess.call(
                ["ngramread", "--ARPA", self.large_arpa_path, self.mod_path], stderr=log_file
            )

        self.log_info("Large ngam model parsed!")

        self.prune_large_language_model()
Convert the arpa model to MFA format
Convert the arpa model to MFA format
Convert the arpa model to MFA format
def train(self) -> None:
        self.log_info("Parsing large ngram model...")
        with open(
            os.path.join(self.working_log_directory, "read.log"), "w", encoding="utf8"
        ) as log_file:
            subprocess.call(
                ["ngramread", "--ARPA", self.large_arpa_path, self.mod_path], stderr=log_file
            )
        self.log_info("Large ngam model parsed!")
        self.prune_large_language_model()
def train ( self ) -> None : self . log_info ( "Parsing large ngram model..." ) with open ( os . path . join ( self . working_log_directory , "read.log" ) , "w" , encoding = "utf8" ) as log_file : subprocess . call ( [ "ngramread" , "--ARPA" , self . large_arpa_path , self . mod_path ] , stderr = log_file ) self . log_info ( "Large ngam model parsed!" ) self . prune_large_language_model ( )
Convert the arpa model to MFA format
Convert the arpa model to MFA format
"""Convert the arpa model to MFA format"""
self