Implemented Mozilla DeepSpeech speech-to-text integration [closes #126]

docs/source/backends.rst

@@ -53,6 +53,7 @@ Backends
     platypush/backend/sensor.mcp3008.rst
     platypush/backend/sensor.motion.pwm3901.rst
     platypush/backend/sensor.serial.rst
+    platypush/backend/stt.deepspeech.rst
     platypush/backend/tcp.rst
     platypush/backend/todoist.rst
     platypush/backend/travisci.rst

docs/source/conf.py

@@ -240,6 +240,7 @@ autodoc_mock_imports = ['googlesamples.assistant.grpc.audio_helpers',
                         'cpuinfo',
                         'psutil',
                         'openzwave',
+                        'deepspeech',
                         ]
 
 sys.path.insert(0, os.path.abspath('../..'))

docs/source/events.rst

@@ -45,6 +45,7 @@ Events
     platypush/events/sensor.light.rst
     platypush/events/serial.rst
     platypush/events/sound.rst
+    platypush/events/stt.rst
     platypush/events/todoist.rst
     platypush/events/torrent.rst
     platypush/events/travisci.rst

docs/source/platypush/backend/stt.deepspeech.rst

@@ -0,0 +1,5 @@
+``platypush.backend.stt.deepspeech``
+====================================
+
+.. automodule:: platypush.backend.stt.deepspeech
+    :members:

docs/source/platypush/events/stt.rst

@@ -0,0 +1,5 @@
+``platypush.message.event.stt``
+===============================
+
+.. automodule:: platypush.message.event.stt
+    :members:

docs/source/platypush/plugins/stt.deepspeech.rst

@@ -0,0 +1,5 @@
+``platypush.plugins.stt.deepspeech``
+====================================
+
+.. automodule:: platypush.plugins.stt.deepspeech
+    :members:

docs/source/platypush/responses/stt.rst

@@ -0,0 +1,5 @@
+``platypush.message.response.stt``
+==================================
+
+.. automodule:: platypush.message.response.stt
+    :members:

docs/source/plugins.rst

@@ -90,6 +90,7 @@ Plugins
     platypush/plugins/serial.rst
     platypush/plugins/shell.rst
     platypush/plugins/sound.rst
+    platypush/plugins/stt.deepspeech.rst
     platypush/plugins/switch.rst
     platypush/plugins/switch.switchbot.rst
     platypush/plugins/switch.tplink.rst

docs/source/responses.rst

@@ -6,15 +6,16 @@ Responses
     :maxdepth: 2
     :caption: Responses:
 
+    platypush/responses/.rst
     platypush/responses/bluetooth.rst
     platypush/responses/camera.rst
     platypush/responses/camera.android.rst
     platypush/responses/chat.telegram.rst
-    platypush/responses/deepspeech.rst
     platypush/responses/google.drive.rst
     platypush/responses/pihole.rst
     platypush/responses/ping.rst
     platypush/responses/printer.cups.rst
+    platypush/responses/stt.rst
     platypush/responses/system.rst
     platypush/responses/todoist.rst
     platypush/responses/trello.rst

platypush/backend/stt/deepspeech.py

@@ -0,0 +1,48 @@
+import time
+
+from platypush.backend import Backend
+from platypush.context import get_plugin
+from platypush.plugins.stt.deepspeech import SttDeepspeechPlugin
+
+
+class SttDeepspeechBackend(Backend):
+    """
+    Backend for the Mozilla Deepspeech speech-to-text engine plugin. Set this plugin to ``enabled`` if you
+    want to run the speech-to-text engine continuously instead of programmatically using
+    ``start_detection`` and ``stop_detection``.
+
+    Requires:
+
+        - The :class:`platypush.plugins.stt.deepspeech.SttDeepspeechPlugin` plugin configured and its dependencies
+          installed, as well as the language model files.
+
+    """
+
+    def __init__(self, retry_sleep: float = 5.0, *args, **kwargs):
+        """
+        :param retry_sleep: Number of seconds the backend will wait on failure before re-initializing the plugin
+            (default: 5 seconds).
+        """
+        super().__init__(*args, **kwargs)
+        self.retry_sleep = retry_sleep
+
+    def run(self):
+        super().run()
+        self.logger.info('Starting Mozilla Deepspeech speech-to-text backend')
+
+        while not self.should_stop():
+            try:
+                plugin: SttDeepspeechPlugin = get_plugin('stt.deepspeech')
+                with plugin:
+                    plugin.start_detection()
+                    # noinspection PyProtectedMember
+                    plugin._detection_thread.join()
+            except Exception as e:
+                self.logger.exception(e)
+                self.logger.warning('Deepspeech backend encountered an unexpected error, retrying in {} seconds'.
+                                    format(self.retry_sleep))
+
+                time.sleep(self.retry_sleep)
+
+
+# vim:sw=4:ts=4:et:

platypush/message/event/stt.py

@@ -0,0 +1,61 @@
+from platypush.message.event import Event
+
+
+class SttEvent(Event):
+    """ Base class for speech-to-text events """
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+
+class SpeechStartedEvent(SttEvent):
+    """
+    Event triggered when speech starts being detected.
+    """
+    pass
+
+
+class SpeechDetectedEvent(SttEvent):
+    """
+    Event triggered when speech is detected.
+    """
+
+    def __init__(self, speech: str, *args, **kwargs):
+        """
+        :param speech: Speech detected, as a string
+        """
+        super().__init__(*args, speech=speech.strip(), **kwargs)
+
+
+class ConversationDetectedEvent(SpeechDetectedEvent):
+    """
+    Event triggered when speech is detected after a hotword.
+    """
+    pass
+
+class HotwordDetectedEvent(SttEvent):
+    """
+    Event triggered when a custom hotword is detected.
+    """
+
+    def __init__(self, hotword: str = '', *args, **kwargs):
+        """
+        :param hotword: The detected user hotword.
+        """
+        super().__init__(*args, hotword=hotword, **kwargs)
+
+
+class SpeechDetectionStartedEvent(SttEvent):
+    """
+    Event triggered when the speech detection engine starts.
+    """
+    pass
+
+
+class SpeechDetectionStoppedEvent(SttEvent):
+    """
+    Event triggered when the speech detection engine stops.
+    """
+    pass
+
+
+# vim:sw=4:ts=4:et:

platypush/message/response/stt.py

@@ -0,0 +1,11 @@
+from platypush.message.response import Response
+
+
+class SpeechDetectedResponse(Response):
+    def __init__(self, *args, speech: str, **kwargs):
+        super().__init__(*args, output={
+            'speech': speech
+        }, **kwargs)
+
+
+# vim:sw=4:ts=4:et:

platypush/plugins/stt/deepspeech.py

@@ -0,0 +1,324 @@
+from __future__ import annotations
+
+import queue
+import os
+import threading
+from typing import Optional, Union, List
+
+import deepspeech
+import numpy as np
+import sounddevice as sd
+import wave
+
+from platypush.context import get_bus
+from platypush.message.event.stt import SpeechDetectionStartedEvent, SpeechDetectionStoppedEvent, SpeechStartedEvent, \
+    SpeechDetectedEvent, HotwordDetectedEvent, ConversationDetectedEvent
+from platypush.message.response.stt import SpeechDetectedResponse
+from platypush.plugins import Plugin, action
+
+
+class SttDeepspeechPlugin(Plugin):
+    """
+    This plugin performs speech-to-text and speech detection using the
+    `Mozilla DeepSpeech <https://github.com/mozilla/DeepSpeech>`_ engine.
+
+    Triggers:
+
+        * :class:`platypush.message.event.stt.SpeechStartedEvent` when speech starts being detected.
+        * :class:`platypush.message.event.stt.SpeechDetectedEvent` when speech is detected.
+        * :class:`platypush.message.event.stt.SpeechDetectionStartedEvent` when speech detection starts.
+        * :class:`platypush.message.event.stt.SpeechDetectionStoppedEvent` when speech detection stops.
+        * :class:`platypush.message.event.stt.HotwordDetectedEvent` when a user-defined hotword is detected.
+        * :class:`platypush.message.event.stt.ConversationDetectedEvent` when speech is detected after a hotword.
+
+    Requires:
+
+        * **deepspeech** (``pip install 'deepspeech>=0.6.0'``)
+        * **numpy** (``pip install numpy``)
+        * **sounddevice** (``pip install sounddevice``)
+
+    """
+
+    _thread_stop_timeout = 10.0
+    rate = 16000
+    channels = 1
+
+    def __init__(self,
+                 model_file: str,
+                 lm_file: str,
+                 trie_file: str,
+                 lm_alpha: float = 0.75,
+                 lm_beta: float = 1.85,
+                 beam_width: int = 500,
+                 input_device: Optional[Union[int, str]] = None,
+                 hotword: Optional[str] = None,
+                 hotwords: Optional[List[str]] = None,
+                 conversation_timeout: Optional[float] = None,
+                 block_duration: float = 1.0):
+        """
+        In order to run the speech-to-text engine you'll need to download the right model files for the
+        Deepspeech engine that you have installed:
+
+        .. code-block:: shell
+
+            # Create the working folder for the models
+            export MODELS_DIR=~/models
+            mkdir -p $MODELS_DIR
+            cd $MODELS_DIR
+
+            # Download and extract the model files for your version of Deepspeech. This may take a while.
+            export DEEPSPEECH_VERSION=0.6.1
+            wget https://github.com/mozilla/DeepSpeech/releases/download/v$DEEPSPEECH_VERSION/deepspeech-$DEEPSPEECH_VERSION-models.tar.gz
+            tar -xvzf deepspeech-$DEEPSPEECH_VERSION-models.tar.gz
+            x deepspeech-0.6.1-models/
+            x deepspeech-0.6.1-models/lm.binary
+            x deepspeech-0.6.1-models/output_graph.pbmm
+            x deepspeech-0.6.1-models/output_graph.pb
+            x deepspeech-0.6.1-models/trie
+            x deepspeech-0.6.1-models/output_graph.tflite
+
+        :param model_file: Path to the model file (usually named ``output_graph.pb`` or ``output_graph.pbmm``).
+            Note that ``.pbmm`` usually perform better and are smaller.
+
+        :param lm_file: Path to the language model binary file (usually named ``lm.binary``).
+        :param trie_file: The path to the trie file build from the same vocabulary as the language model binary
+            (usually named ``trie``).
+        :param lm_alpha: The alpha hyperparameter of the CTC decoder - Language Model weight.
+            See <https://github.com/mozilla/DeepSpeech/releases/tag/v0.6.0>.
+        :param lm_beta: The beta hyperparameter of the CTC decoder - Word Insertion weight.
+            See <https://github.com/mozilla/DeepSpeech/releases/tag/v0.6.0>.
+        :param beam_width:  Decoder beam width (see beam scoring in KenLM language model).
+        :param input_device: PortAudio device index or name that will be used for recording speech (default: default
+            system audio input device).
+        :param hotword: When this word is detected, the plugin will trigger a
+            :class:`platypush.message.event.stt.HotwordDetectedEvent` instead of a
+            :class:`platypush.message.event.stt.SpeechDetectedEvent` event. You can use these events for hooking other
+            assistants.
+        :param hotwords: Use a list of hotwords instead of a single one.
+        :param conversation_timeout: If ``hotword`` or ``hotwords`` are set and ``conversation_timeout`` is set,
+            the next speech detected event will trigger a :class:`platypush.message.event.stt.ConversationDetectedEvent`
+            instead of a :class:`platypush.message.event.stt.SpeechDetectedEvent` event. You can hook custom hooks
+            here to run any logic depending on the detected speech - it can emulate a kind of
+            "OK, Google. Turn on the lights" interaction without using an external assistant.
+        :param block_duration: Duration of the acquired audio blocks (default: 1 second).
+        """
+
+        super().__init__()
+        self.model_file = os.path.abspath(os.path.expanduser(model_file))
+        self.lm_file = os.path.abspath(os.path.expanduser(lm_file))
+        self.trie_file = os.path.abspath(os.path.expanduser(trie_file))
+        self.lm_alpha = lm_alpha
+        self.lm_beta = lm_beta
+        self.beam_width = beam_width
+        self.input_device = input_device
+        self.conversation_timeout = conversation_timeout
+        self.block_duration = block_duration
+
+        self.hotwords = set(hotwords or [])
+        if hotword:
+            self.hotwords = {hotword}
+
+        self._conversation_event = threading.Event()
+        self._model: Optional[deepspeech.Model] = None
+        self._input_stream: Optional[sd.InputStream] = None
+        self._recording_thread: Optional[threading.Thread] = None
+        self._detection_thread: Optional[threading.Thread] = None
+        self._audio_queue: Optional[queue.Queue] = None
+
+    def _get_model(self) -> deepspeech.Model:
+        if not self._model:
+            self._model = deepspeech.Model(self.model_file, self.beam_width)
+            self._model.enableDecoderWithLM(self.lm_file, self.trie_file, self.lm_alpha, self.lm_beta)
+
+        return self._model
+
+    def _detect(self, data: Union[bytes, np.ndarray]) -> str:
+        data = self._convert_data(data)
+        model = self._get_model()
+        return model.stt(data)
+
+    @staticmethod
+    def _convert_data(data: Union[np.ndarray, bytes]) -> np.ndarray:
+        return np.frombuffer(data, dtype=np.int16)
+
+    def _get_input_device(self, device: Optional[Union[int, str]] = None) -> int:
+        """
+        Get the index of the input device by index or name.
+
+        :param device: Device index or name. If None is set then the function will return the index of the
+            default audio input device.
+        :return: Index of the audio input device.
+        """
+        if not device:
+            device = self.input_device
+        if not device:
+            return sd.query_hostapis()[0].get('default_input_device')
+
+        if isinstance(device, int):
+            assert device <= len(sd.query_devices())
+            return device
+
+        for i, dev in enumerate(sd.query_devices()):
+            if dev['name'] == device:
+                return i
+
+        raise AssertionError('Device {} not found'.format(device))
+
+    def _on_speech_detected(self, speech: str) -> None:
+        """
+        Hook called when speech is detected. Triggers the right event depending on the current context.
+
+        :param speech: Detected speech.
+        """
+        speech = speech.strip()
+
+        if self._conversation_event.is_set():
+            event = ConversationDetectedEvent(speech=speech)
+        elif speech in self.hotwords:
+            event = HotwordDetectedEvent(hotword=speech)
+            if self.conversation_timeout:
+                self._conversation_event.set()
+                threading.Timer(self.conversation_timeout, lambda: self._conversation_event.clear()).start()
+        else:
+            event = SpeechDetectedEvent(speech=speech)
+
+        get_bus().post(event)
+
+    def detection_thread(self) -> None:
+        """
+        Speech detection thread. Reads from the ``audio_queue`` and uses the Deepspeech model to detect
+        speech real-time.
+        """
+        self.logger.debug('Detection thread started')
+        model = self._get_model()
+        current_text = ''
+        context = None
+
+        while self._audio_queue:
+            if not context:
+                context = model.createStream()
+
+            try:
+                frames = self._audio_queue.get()
+                frames = self._convert_data(frames)
+            except Exception as e:
+                self.logger.warning('Error while feeding audio to the model: {}'.format(str(e)))
+                continue
+
+            model.feedAudioContent(context, frames)
+            text = model.intermediateDecode(context)
+
+            if text == current_text:
+                if current_text:
+                    self._on_speech_detected(current_text)
+                    model.finishStream(context)
+                    context = None
+
+                current_text = ''
+            else:
+                if not current_text:
+                    get_bus().post(SpeechStartedEvent())
+
+                self.logger.info('Intermediate speech results: [{}]'.format(text))
+                current_text = text
+
+        self.logger.debug('Detection thread terminated')
+
+    def recording_thread(self, block_duration: float, input_device: Optional[str] = None) -> None:
+        """
+        Recording thread. It reads raw frames from the audio device and dispatches them to ``detection_thread``.
+
+        :param block_duration: Audio blocks duration.
+        :param input_device: Input device
+        """
+        self.logger.debug('Recording thread started')
+        device = self._get_input_device(input_device)
+        blocksize = int(self.rate * self.channels * block_duration)
+        self._input_stream = sd.InputStream(samplerate=self.rate, device=device,
+                                            channels=self.channels, dtype='int16', latency=0,
+                                            blocksize=blocksize)
+        self._input_stream.start()
+        get_bus().post(SpeechDetectionStartedEvent())
+
+        while self._input_stream:
+            try:
+                frames = self._input_stream.read(self.rate)[0]
+            except Exception as e:
+                self.logger.warning('Error while reading from the audio input: {}'.format(str(e)))
+                continue
+
+            self._audio_queue.put(frames)
+
+        get_bus().post(SpeechDetectionStoppedEvent())
+        self.logger.debug('Recording thread terminated')
+
+    @action
+    def detect(self, audio_file: str) -> SpeechDetectedResponse:
+        """
+        Perform speech-to-text analysis on an audio file.
+
+        :param audio_file: Path to the audio file.
+        """
+        audio_file = os.path.abspath(os.path.expanduser(audio_file))
+        wav = wave.open(audio_file, 'r')
+        buffer = wav.readframes(wav.getnframes())
+        speech = self._detect(buffer)
+        return SpeechDetectedResponse(speech=speech)
+
+    def __enter__(self) -> SttDeepspeechPlugin:
+        """
+        Context manager enter. Starts detection and returns self.
+        """
+        self.start_detection()
+        return self
+
+    def __exit__(self, exc_type, exc_val, exc_tb):
+        """
+        Context manager exit. Stops detection.
+        """
+        self.stop_detection()
+
+    @action
+    def start_detection(self, input_device: Optional[str] = None, seconds: Optional[float] = None,
+                        block_duration: Optional[float] = None) -> None:
+        """
+        Start the speech detection engine.
+
+        :param input_device: Audio input device name/index override
+        :param seconds: If set, then the detection engine will stop after this many seconds, otherwise it'll
+            start running until ``stop_detection`` is called or application stop.
+        :param block_duration: ``block_duration`` override.
+        """
+        assert not self._input_stream, 'Speech detection is already running'
+        block_duration = block_duration or self.block_duration
+        input_device = input_device if input_device is not None else self.input_device
+        self._audio_queue = queue.Queue()
+        self._recording_thread = threading.Thread(
+            target=lambda: self.recording_thread(block_duration=block_duration, input_device=input_device))
+
+        self._recording_thread.start()
+        self._detection_thread = threading.Thread(target=lambda: self.detection_thread())
+        self._detection_thread.start()
+
+        if seconds:
+            threading.Timer(seconds, lambda: self.stop_detection()).start()
+
+    @action
+    def stop_detection(self) -> None:
+        """
+        Stop the speech detection engine.
+        """
+        assert self._input_stream, 'Speech detection is not running'
+        self._input_stream.stop(ignore_errors=True)
+        self._input_stream.close(ignore_errors=True)
+        self._input_stream = None
+
+        if self._recording_thread:
+            self._recording_thread.join(timeout=self._thread_stop_timeout)
+
+        self._audio_queue = None
+        if self._detection_thread:
+            self._detection_thread.join(timeout=self._thread_stop_timeout)
+
+
+# vim:sw=4:ts=4:et:

requirements.txt

@@ -229,3 +229,8 @@ croniter
 
 # Support for Z-Wave
 # python-openzwave
+
+# Support for DeepSpeech
+# deepspeech
+# numpy
+# sounddevice

setup.py

@@ -283,5 +283,7 @@ setup(
         'zigbee': ['paho-mqtt'],
         # Support for Z-Wave
         'zwave': ['python-openzwave'],
+        # Support for DeepSpeech
+        'deepspeech': ['deepspeech', 'numpy','sounddevice'],
     },
 )