local_recognizer.py

# Copyright 2016 Mycroft AI, Inc.
#
# This file is part of Mycroft Core.
#
# Mycroft Core is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Mycroft Core is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Mycroft Core.  If not, see <http://www.gnu.org/licenses/>.


import time

import os
from pocketsphinx import Decoder, get_model_path
import tempfile

__author__ = 'seanfitz, jdorleans'

MODELDIR = 'model'

class LocalRecognizer(object):
    def __init__(self, key_phrase, phonemes, threshold, sample_rate=16000,
                 lang="en-us"):
        self.lang = lang
        self.key_phrase = key_phrase
        self.sample_rate = sample_rate
        self.threshold = threshold
        self.phonemes = phonemes
        dict_name = self.create_dict(key_phrase, phonemes)
        self.decoder = Decoder(self.create_config(dict_name))

    def create_dict(self, key_phrase, phonemes):
        (fd, file_name) = tempfile.mkstemp()
        words = key_phrase.split()
        phoneme_groups = phonemes.split('.')
        with os.fdopen(fd, 'w') as f:
            for word, phoneme in zip(words, phoneme_groups):
                f.write(word + ' ' + phoneme + '\n')
        return file_name

    def create_config(self, dict_name):
        config = Decoder.default_config()
        config.set_string('-hmm', os.path.join(MODELDIR, 'en-us'))
        config.set_string('-dict', dict_name)
        config.set_string('-keyphrase', self.key_phrase)
        config.set_float('-kws_threshold', float(self.threshold))
        config.set_float('-samprate', self.sample_rate)
        config.set_int('-nfft', 2048)
        config.set_string('-logfn', '/dev/null')
        return config

    def transcribe(self, byte_data, metrics=None):
        start = time.time()
        self.decoder.start_utt()
        self.decoder.process_raw(byte_data, False, False)
        self.decoder.end_utt()
        if metrics:
            metrics.timer("mycroft.stt.local.time_s", time.time() - start)
        return self.decoder.hyp()

    def is_recognized(self, byte_data, metrics):
        hyp = self.transcribe(byte_data, metrics)
        return hyp and self.key_phrase in hyp.hypstr.lower()

    def found_wake_word(self, hypothesis):
        return hypothesis and self.key_phrase in hypothesis.hypstr.lower()