77 lines
2.7 KiB
Python
77 lines
2.7 KiB
Python
# Copyright 2016 Mycroft AI, Inc.
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#
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# This file is part of Mycroft Core.
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#
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# Mycroft Core is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# Mycroft Core is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with Mycroft Core. If not, see <http://www.gnu.org/licenses/>.
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import os
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import tempfile
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import time
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from os.path import join, dirname, abspath
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from pocketsphinx import Decoder
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__author__ = 'seanfitz, jdorleans'
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BASEDIR = dirname(abspath(__file__))
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class LocalRecognizer(object):
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def __init__(self, key_phrase, phonemes, threshold, sample_rate=16000,
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lang="en-us"):
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self.lang = str(lang)
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self.key_phrase = str(key_phrase)
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self.sample_rate = sample_rate
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self.threshold = threshold
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self.phonemes = phonemes
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dict_name = self.create_dict(key_phrase, phonemes)
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self.decoder = Decoder(self.create_config(dict_name))
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def create_dict(self, key_phrase, phonemes):
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(fd, file_name) = tempfile.mkstemp()
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words = key_phrase.split()
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phoneme_groups = phonemes.split('.')
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with os.fdopen(fd, 'w') as f:
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for word, phoneme in zip(words, phoneme_groups):
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f.write(word + ' ' + phoneme + '\n')
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return file_name
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def create_config(self, dict_name):
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config = Decoder.default_config()
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config.set_string('-hmm', join(BASEDIR, 'model', self.lang, 'hmm'))
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config.set_string('-dict', dict_name)
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config.set_string('-keyphrase', self.key_phrase)
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config.set_float('-kws_threshold', self.threshold)
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config.set_float('-samprate', self.sample_rate)
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config.set_int('-nfft', 2048)
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config.set_string('-logfn', '/dev/null')
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return config
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def transcribe(self, byte_data, metrics=None):
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start = time.time()
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self.decoder.start_utt()
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self.decoder.process_raw(byte_data, False, False)
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self.decoder.end_utt()
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if metrics:
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metrics.timer("mycroft.stt.local.time_s", time.time() - start)
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return self.decoder.hyp()
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def is_recognized(self, byte_data, metrics):
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hyp = self.transcribe(byte_data, metrics)
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return hyp and self.key_phrase in hyp.hypstr.lower()
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def found_wake_word(self, hypothesis):
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return hypothesis and self.key_phrase in hypothesis.hypstr.lower()
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