# 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 . import os import tempfile import time from os.path import join, dirname, abspath from pocketsphinx import Decoder __author__ = 'seanfitz, jdorleans' BASEDIR = dirname(abspath(__file__)) class LocalRecognizer(object): def __init__(self, key_phrase, phonemes, threshold, sample_rate=16000, lang="en-us"): self.lang = str(lang) self.key_phrase = str(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', join(BASEDIR, 'model', self.lang, 'hmm')) config.set_string('-dict', dict_name) config.set_string('-keyphrase', self.key_phrase) config.set_float('-kws_threshold', 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()