Removed stt.deepspeech integration.

The project hasn't seen a commit in three years and it's probably been
abandoned by Mozilla.

New and better maintained speech-to-text integrations will be
investigated.

docs/source/backends.rst

@@ -10,7 +10,6 @@ Backends
     platypush/backend/midi.rst
     platypush/backend/nodered.rst
     platypush/backend/redis.rst
-    platypush/backend/stt.deepspeech.rst
     platypush/backend/stt.picovoice.hotword.rst
     platypush/backend/stt.picovoice.speech.rst
     platypush/backend/tcp.rst

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

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

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

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

docs/source/plugins.rst

@@ -119,7 +119,6 @@ Plugins
     platypush/plugins/smartthings.rst
     platypush/plugins/sound.rst
     platypush/plugins/ssh.rst
-    platypush/plugins/stt.deepspeech.rst
     platypush/plugins/stt.picovoice.hotword.rst
     platypush/plugins/stt.picovoice.speech.rst
     platypush/plugins/sun.rst

platypush/backend/stt/deepspeech/__init__.py

@@ -1,21 +0,0 @@
-from platypush.backend.stt import SttBackend
-
-
-class SttDeepspeechBackend(SttBackend):
-    """
-    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, *args, **kwargs):
-        super().__init__('stt.deepspeech', *args, **kwargs)
-
-
-# vim:sw=4:ts=4:et:

platypush/backend/stt/deepspeech/manifest.yaml

@@ -1,6 +0,0 @@
-manifest:
-  events: {}
-  install:
-    pip: []
-  package: platypush.backend.stt.deepspeech
-  type: backend

platypush/plugins/stt/deepspeech/__init__.py

@@ -1,153 +0,0 @@
-import os
-from typing import Optional, Union
-
-import numpy as np
-import wave
-
-from platypush.message.response.stt import SpeechDetectedResponse
-from platypush.plugins import action
-from platypush.plugins.stt import SttPlugin
-
-
-class SttDeepspeechPlugin(SttPlugin):
-    """
-    This plugin performs speech-to-text and speech detection using the
-    `Mozilla DeepSpeech <https://github.com/mozilla/DeepSpeech>`_ engine.
-    """
-
-    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,
-        *args,
-        **kwargs
-    ):
-        """
-        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).
-        """
-
-        import deepspeech
-
-        super().__init__(*args, **kwargs)
-        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._model: Optional[deepspeech.Model] = None
-        self._context = None
-
-    def _get_model(self):
-        import deepspeech
-
-        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 _get_context(self):
-        if not self._model:
-            self._model = self._get_model()
-        if not self._context:
-            self._context = self._model.createStream()
-
-        return self._context
-
-    @staticmethod
-    def convert_frames(frames: Union[np.ndarray, bytes]) -> np.ndarray:
-        return np.frombuffer(frames, dtype=np.int16)
-
-    def on_detection_started(self):
-        self._context = self._get_context()
-
-    def on_detection_ended(self):
-        if self._model and self._context:
-            self._model.finishStream()
-        self._context = None
-
-    def detect_speech(self, frames) -> str:
-        model = self._get_model()
-        context = self._get_context()
-        model.feedAudioContent(context, frames)
-        return model.intermediateDecode(context)
-
-    def on_speech_detected(self, speech: str) -> None:
-        super().on_speech_detected(speech)
-        if not speech:
-            return
-
-        model = self._get_model()
-        context = self._get_context()
-        model.finishStream(context)
-        self._context = None
-
-    @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())
-        data = self.convert_frames(buffer)
-        model = self._get_model()
-        speech = model.stt(data)
-        return SpeechDetectedResponse(speech=speech)
-
-
-# vim:sw=4:ts=4:et:

platypush/plugins/stt/deepspeech/manifest.yaml

@@ -1,18 +0,0 @@
-manifest:
-  events: {}
-  install:
-    apk:
-      - py3-numpy
-    pacman:
-      - python-numpy
-      - python-sounddevice
-    apt:
-      - python3-numpy
-    dnf:
-      - python-numpy
-    pip:
-      - deepspeech
-      - numpy
-      - sounddevice
-  package: platypush.plugins.stt.deepspeech
-  type: plugin