mycroft-core/mycroft/tts/__init__.py

493 lines
15 KiB
Python

# Copyright 2017 Mycroft AI Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import hashlib
import os
import random
import re
import sys
from abc import ABCMeta, abstractmethod
from threading import Thread
from time import time, sleep
import os.path
from os.path import dirname, exists, isdir, join
import mycroft.util
from mycroft.enclosure.api import EnclosureAPI
from mycroft.configuration import Configuration
from mycroft.messagebus.message import Message
from mycroft.metrics import report_timing, Stopwatch
from mycroft.util import (
play_wav, play_mp3, check_for_signal, create_signal, resolve_resource_file
)
from mycroft.util.log import LOG
from queue import Queue, Empty
def send_playback_metric(stopwatch, ident):
"""
Send playback metrics in a background thread
"""
def do_send(stopwatch, ident):
report_timing(ident, 'speech_playback', stopwatch)
t = Thread(target=do_send, args=(stopwatch, ident))
t.daemon = True
t.start()
class PlaybackThread(Thread):
"""
Thread class for playing back tts audio and sending
viseme data to enclosure.
"""
def __init__(self, queue):
super(PlaybackThread, self).__init__()
self.queue = queue
self._terminated = False
self._processing_queue = False
def init(self, tts):
self.tts = tts
def clear_queue(self):
"""
Remove all pending playbacks.
"""
while not self.queue.empty():
self.queue.get()
try:
self.p.terminate()
except:
pass
def run(self):
"""
Thread main loop. get audio and viseme data from queue
and play.
"""
while not self._terminated:
try:
snd_type, data, visemes, ident = self.queue.get(timeout=2)
self.blink(0.5)
if not self._processing_queue:
self._processing_queue = True
self.tts.begin_audio()
stopwatch = Stopwatch()
with stopwatch:
if snd_type == 'wav':
self.p = play_wav(data)
elif snd_type == 'mp3':
self.p = play_mp3(data)
if visemes:
self.show_visemes(visemes)
self.p.communicate()
self.p.wait()
send_playback_metric(stopwatch, ident)
if self.queue.empty():
self.tts.end_audio()
self._processing_queue = False
self.blink(0.2)
except Empty:
pass
except Exception as e:
LOG.exception(e)
if self._processing_queue:
self.tts.end_audio()
self._processing_queue = False
def show_visemes(self, pairs):
"""
Send viseme data to enclosure
Args:
pairs(list): Visime and timing pair
Returns:
True if button has been pressed.
"""
if self.enclosure:
self.enclosure.mouth_viseme(time(), pairs)
def clear(self):
""" Clear all pending actions for the TTS playback thread. """
self.clear_queue()
def blink(self, rate=1.0):
""" Blink mycroft's eyes """
if self.enclosure and random.random() < rate:
self.enclosure.eyes_blink("b")
def stop(self):
""" Stop thread """
self._terminated = True
self.clear_queue()
class TTS:
"""
TTS abstract class to be implemented by all TTS engines.
It aggregates the minimum required parameters and exposes
``execute(sentence)`` and ``validate_ssml(sentence)`` functions.
Args:
lang (str):
config (dict): Configuration for this specific tts engine
validator (TTSValidator): Used to verify proper installation
phonetic_spelling (bool): Whether to spell certain words phonetically
ssml_tags (list): Supported ssml properties. Ex. ['speak', 'prosody']
"""
__metaclass__ = ABCMeta
def __init__(self, lang, config, validator, audio_ext='wav',
phonetic_spelling=True, ssml_tags=None):
super(TTS, self).__init__()
self.bus = None # initalized in "init" step
self.lang = lang or 'en-us'
self.config = config
self.validator = validator
self.phonetic_spelling = phonetic_spelling
self.audio_ext = audio_ext
self.ssml_tags = ssml_tags or []
self.voice = config.get("voice")
self.filename = '/tmp/tts.wav'
self.enclosure = None
random.seed()
self.queue = Queue()
self.playback = PlaybackThread(self.queue)
self.playback.start()
self.clear_cache()
self.spellings = self.load_spellings()
self.tts_name = type(self).__name__
def load_spellings(self):
"""Load phonetic spellings of words as dictionary"""
path = join('text', self.lang, 'phonetic_spellings.txt')
spellings_file = resolve_resource_file(path)
if not spellings_file:
return {}
try:
with open(spellings_file) as f:
lines = filter(bool, f.read().split('\n'))
lines = [i.split(':') for i in lines]
return {key.strip(): value.strip() for key, value in lines}
except ValueError:
LOG.exception('Failed to load phonetic spellings.')
return {}
def begin_audio(self):
"""Helper function for child classes to call in execute()"""
# Create signals informing start of speech
self.bus.emit(Message("recognizer_loop:audio_output_start"))
def end_audio(self):
"""
Helper function for child classes to call in execute().
Sends the recognizer_loop:audio_output_end message, indicating
that speaking is done for the moment. It also checks if cache
directory needs cleaning to free up disk space.
"""
self.bus.emit(Message("recognizer_loop:audio_output_end"))
# Clean the cache as needed
cache_dir = mycroft.util.get_cache_directory("tts/" + self.tts_name)
mycroft.util.curate_cache(cache_dir, min_free_percent=100)
# This check will clear the "signal"
check_for_signal("isSpeaking")
def init(self, bus):
""" Performs intial setup of TTS object.
Arguments:
bus: Mycroft messagebus connection
"""
self.bus = bus
self.playback.init(self)
self.enclosure = EnclosureAPI(self.bus)
self.playback.enclosure = self.enclosure
def get_tts(self, sentence, wav_file):
"""
Abstract method that a tts implementation needs to implement.
Should get data from tts.
Args:
sentence(str): Sentence to synthesize
wav_file(str): output file
Returns:
tuple: (wav_file, phoneme)
"""
pass
def modify_tag(self, tag):
"""Override to modify each supported ssml tag"""
return tag
@staticmethod
def remove_ssml(text):
return re.sub('<[^>]*>', '', text).replace(' ', ' ')
def validate_ssml(self, utterance):
"""
Check if engine supports ssml, if not remove all tags
Remove unsupported / invalid tags
Args:
utterance(str): Sentence to validate
Returns: validated_sentence (str)
"""
# if ssml is not supported by TTS engine remove all tags
if not self.ssml_tags:
return self.remove_ssml(utterance)
# find ssml tags in string
tags = re.findall('<[^>]*>', utterance)
for tag in tags:
if any(supported in tag for supported in self.ssml_tags):
utterance = utterance.replace(tag, self.modify_tag(tag))
else:
# remove unsupported tag
utterance = utterance.replace(tag, "")
# return text with supported ssml tags only
return utterance.replace(" ", " ")
def _preprocess_sentence(self, sentence):
""" Default preprocessing is no preprocessing.
This method can be overridden to create chunks suitable to the
TTS engine in question.
Arguments:
sentence (str): sentence to preprocess
Returns:
list: list of sentence parts
"""
return [sentence]
def execute(self, sentence, ident=None):
"""
Convert sentence to speech, preprocessing out unsupported ssml
The method caches results if possible using the hash of the
sentence.
Args:
sentence: Sentence to be spoken
ident: Id reference to current interaction
"""
sentence = self.validate_ssml(sentence)
create_signal("isSpeaking")
if self.phonetic_spelling:
for word in re.findall(r"[\w']+", sentence):
if word.lower() in self.spellings:
sentence = sentence.replace(word,
self.spellings[word.lower()])
chunks = self._preprocess_sentence(sentence)
for sentence in chunks:
key = str(hashlib.md5(
sentence.encode('utf-8', 'ignore')).hexdigest())
wav_file = os.path.join(
mycroft.util.get_cache_directory("tts/" + self.tts_name),
key + '.' + self.audio_ext)
if os.path.exists(wav_file):
LOG.debug("TTS cache hit")
phonemes = self.load_phonemes(key)
else:
wav_file, phonemes = self.get_tts(sentence, wav_file)
if phonemes:
self.save_phonemes(key, phonemes)
vis = self.viseme(phonemes)
self.queue.put((self.audio_ext, wav_file, vis, ident))
def viseme(self, phonemes):
"""
Create visemes from phonemes. Needs to be implemented for all
tts backend
Args:
phonemes(str): String with phoneme data
"""
return None
def clear_cache(self):
""" Remove all cached files. """
if not os.path.exists(mycroft.util.get_cache_directory('tts')):
return
for d in os.listdir(mycroft.util.get_cache_directory("tts")):
dir_path = os.path.join(mycroft.util.get_cache_directory("tts"), d)
if os.path.isdir(dir_path):
for f in os.listdir(dir_path):
file_path = os.path.join(dir_path, f)
if os.path.isfile(file_path):
os.unlink(file_path)
# If no sub-folders are present, check if it is a file & clear it
elif os.path.isfile(dir_path):
os.unlink(dir_path)
def save_phonemes(self, key, phonemes):
"""
Cache phonemes
Args:
key: Hash key for the sentence
phonemes: phoneme string to save
"""
cache_dir = mycroft.util.get_cache_directory("tts/" + self.tts_name)
pho_file = os.path.join(cache_dir, key + ".pho")
try:
with open(pho_file, "w") as cachefile:
cachefile.write(phonemes)
except Exception:
LOG.exception("Failed to write {} to cache".format(pho_file))
pass
def load_phonemes(self, key):
"""
Load phonemes from cache file.
Args:
Key: Key identifying phoneme cache
"""
pho_file = os.path.join(
mycroft.util.get_cache_directory("tts/" + self.tts_name),
key + ".pho")
if os.path.exists(pho_file):
try:
with open(pho_file, "r") as cachefile:
phonemes = cachefile.read().strip()
return phonemes
except:
LOG.debug("Failed to read .PHO from cache")
return None
def __del__(self):
self.playback.stop()
self.playback.join()
class TTSValidator:
"""
TTS Validator abstract class to be implemented by all TTS engines.
It exposes and implements ``validate(tts)`` function as a template to
validate the TTS engines.
"""
__metaclass__ = ABCMeta
def __init__(self, tts):
self.tts = tts
def validate(self):
self.validate_dependencies()
self.validate_instance()
self.validate_filename()
self.validate_lang()
self.validate_connection()
def validate_dependencies(self):
pass
def validate_instance(self):
clazz = self.get_tts_class()
if not isinstance(self.tts, clazz):
raise AttributeError('tts must be instance of ' + clazz.__name__)
def validate_filename(self):
filename = self.tts.filename
if not (filename and filename.endswith('.wav')):
raise AttributeError('file: %s must be in .wav format!' % filename)
dir_path = dirname(filename)
if not (exists(dir_path) and isdir(dir_path)):
raise AttributeError('filename: %s is not valid!' % filename)
@abstractmethod
def validate_lang(self):
pass
@abstractmethod
def validate_connection(self):
pass
@abstractmethod
def get_tts_class(self):
pass
class TTSFactory:
from mycroft.tts.espeak_tts import ESpeak
from mycroft.tts.fa_tts import FATTS
from mycroft.tts.google_tts import GoogleTTS
from mycroft.tts.mary_tts import MaryTTS
from mycroft.tts.mimic_tts import Mimic
from mycroft.tts.spdsay_tts import SpdSay
from mycroft.tts.bing_tts import BingTTS
from mycroft.tts.ibm_tts import WatsonTTS
from mycroft.tts.responsive_voice_tts import ResponsiveVoice
from mycroft.tts.mimic2_tts import Mimic2
CLASSES = {
"mimic": Mimic,
"mimic2": Mimic2,
"google": GoogleTTS,
"marytts": MaryTTS,
"fatts": FATTS,
"espeak": ESpeak,
"spdsay": SpdSay,
"watson": WatsonTTS,
"bing": BingTTS,
"responsive_voice": ResponsiveVoice
}
@staticmethod
def create():
"""
Factory method to create a TTS engine based on configuration.
The configuration file ``mycroft.conf`` contains a ``tts`` section with
the name of a TTS module to be read by this method.
"tts": {
"module": <engine_name>
}
"""
config = Configuration.get()
lang = config.get("lang", "en-us")
tts_module = config.get('tts', {}).get('module', 'mimic')
tts_config = config.get('tts', {}).get(tts_module, {})
tts_lang = tts_config.get('lang', lang)
clazz = TTSFactory.CLASSES.get(tts_module)
tts = clazz(tts_lang, tts_config)
tts.validator.validate()
return tts