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# SPDX-License-Identifier: Apache-2.0
#
# Copyright (c) 2023 Malik Talha
#
# 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 gi
gi.require_version('Gst', '1.0')
from gi.repository import Gst, GLib
Gst.init(None)
GLib.threads_init()
class WakeWordDetector:
"""
WakeWordDetector is a class for detecting a wake word in an audio stream using GStreamer and Vosk.
"""
def __init__(self, wake_word, stt_model, channels=1, sample_rate=16000, bits_per_sample=16):
"""
Initialize the WakeWordDetector instance with the provided parameters.
Args:
wake_word (str): The wake word to detect in the audio stream.
stt_model (STTModel): An instance of the STTModel for speech-to-text recognition.
channels (int, optional): The number of audio channels (default is 1).
sample_rate (int, optional): The audio sample rate in Hz (default is 16000).
bits_per_sample (int, optional): The number of bits per sample (default is 16).
"""
self.loop = GLib.MainLoop()
self.pipeline = None
self.bus = None
self.wake_word = wake_word
self.wake_word_detected = False
self.sample_rate = sample_rate
self.channels = channels
self.bits_per_sample = bits_per_sample
self.wake_word_model = stt_model # Speech to text model recognizer
self.recognizer_uuid = stt_model.setup_recognizer()
self.audio_buffer = bytearray()
self.segment_size = int(self.sample_rate * 1.0) # Adjust the segment size (e.g., 1 second)
def get_wake_word_status(self):
"""
Get the status of wake word detection.
Returns:
bool: True if the wake word has been detected, False otherwise.
"""
return self.wake_word_detected
def create_pipeline(self):
"""
Create and configure the GStreamer audio processing pipeline for wake word detection.
"""
print("Creating pipeline for Wake Word Detection...")
self.pipeline = Gst.Pipeline()
autoaudiosrc = Gst.ElementFactory.make("autoaudiosrc", None)
queue = Gst.ElementFactory.make("queue", None)
audioconvert = Gst.ElementFactory.make("audioconvert", None)
wavenc = Gst.ElementFactory.make("wavenc", None)
capsfilter = Gst.ElementFactory.make("capsfilter", None)
caps = Gst.Caps.new_empty_simple("audio/x-raw")
caps.set_value("format", "S16LE")
caps.set_value("rate", self.sample_rate)
caps.set_value("channels", self.channels)
capsfilter.set_property("caps", caps)
appsink = Gst.ElementFactory.make("appsink", None)
appsink.set_property("emit-signals", True)
appsink.set_property("sync", False) # Set sync property to False to enable async processing
appsink.connect("new-sample", self.on_new_buffer, None)
self.pipeline.add(autoaudiosrc)
self.pipeline.add(queue)
self.pipeline.add(audioconvert)
self.pipeline.add(wavenc)
self.pipeline.add(capsfilter)
self.pipeline.add(appsink)
autoaudiosrc.link(queue)
queue.link(audioconvert)
audioconvert.link(capsfilter)
capsfilter.link(appsink)
self.bus = self.pipeline.get_bus()
self.bus.add_signal_watch()
self.bus.connect("message", self.on_bus_message)
def on_new_buffer(self, appsink, data) -> Gst.FlowReturn:
"""
Callback function to handle new audio buffers from GStreamer appsink.
Args:
appsink (Gst.AppSink): The GStreamer appsink.
data (object): User data (not used).
Returns:
Gst.FlowReturn: Indicates the status of buffer processing.
"""
sample = appsink.emit("pull-sample")
buffer = sample.get_buffer()
data = buffer.extract_dup(0, buffer.get_size())
# Add the new data to the buffer
self.audio_buffer.extend(data)
# Process audio in segments
while len(self.audio_buffer) >= self.segment_size:
segment = self.audio_buffer[:self.segment_size]
self.process_audio_segment(segment)
# Advance the buffer by the segment size
self.audio_buffer = self.audio_buffer[self.segment_size:]
return Gst.FlowReturn.OK
def process_audio_segment(self, segment):
"""
Process an audio segment for wake word detection.
Args:
segment (bytes): The audio segment to process.
"""
# Process the audio data segment
audio_data = bytes(segment)
# Perform wake word detection on the audio_data
if self.wake_word_model.init_recognition(self.recognizer_uuid, audio_data):
stt_result = self.wake_word_model.recognize(self.recognizer_uuid)
print("STT Result: ", stt_result)
if self.wake_word in stt_result["text"]:
self.wake_word_detected = True
print("Wake word detected!")
self.pipeline.send_event(Gst.Event.new_eos())
def send_eos(self):
"""
Send an End-of-Stream (EOS) event to the pipeline.
"""
self.pipeline.send_event(Gst.Event.new_eos())
self.audio_buffer.clear()
def start_listening(self):
"""
Start listening for the wake word and enter the event loop.
"""
self.pipeline.set_state(Gst.State.PLAYING)
print("Listening for Wake Word...")
self.loop.run()
def stop_listening(self):
"""
Stop listening for the wake word and clean up the pipeline.
"""
self.cleanup_pipeline()
self.loop.quit()
def on_bus_message(self, bus, message):
"""
Handle GStreamer bus messages and perform actions based on the message type.
Args:
bus (Gst.Bus): The GStreamer bus.
message (Gst.Message): The GStreamer message to process.
"""
if message.type == Gst.MessageType.EOS:
print("End-of-stream message received")
self.stop_listening()
elif message.type == Gst.MessageType.ERROR:
err, debug_info = message.parse_error()
print(f"Error received from element {message.src.get_name()}: {err.message}")
print(f"Debugging information: {debug_info}")
self.stop_listening()
elif message.type == Gst.MessageType.WARNING:
err, debug_info = message.parse_warning()
print(f"Warning received from element {message.src.get_name()}: {err.message}")
print(f"Debugging information: {debug_info}")
elif message.type == Gst.MessageType.STATE_CHANGED:
if isinstance(message.src, Gst.Pipeline):
old_state, new_state, pending_state = message.parse_state_changed()
print(("Pipeline state changed from %s to %s." %
(old_state.value_nick, new_state.value_nick)))
def cleanup_pipeline(self):
"""
Clean up the GStreamer pipeline and release associated resources.
"""
if self.pipeline is not None:
print("Cleaning up pipeline...")
self.pipeline.set_state(Gst.State.NULL)
self.bus.remove_signal_watch()
print("Pipeline cleanup complete!")
self.bus = None
self.pipeline = None
self.wake_word_model.cleanup_recognizer(self.recognizer_uuid)
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