diff --git a/README.md b/README.md
index e047a363..dfd44d71 100644
--- a/README.md
+++ b/README.md
@@ -500,6 +500,7 @@ Conversation options are represented as features. They can be configured from Ap
 | `slow_llm_for_chat` | Whether to use the slow LLM for chat. | `bool` | false |
 | `vad_cutoff_timeout_ms` | The cutoff timeout for voice activity detection in secs. | `int` | 600 |
 | `vad_silence_timeout_ms` | The timeout for phone silence in secs. | `int` | 400 |
+| `vad_threshold` | The threshold for voice activity detection. | `float` | 0.5 |
 
 ### Use an OpenAI compatible model for the LLM
 
diff --git a/app/helpers/call_events.py b/app/helpers/call_events.py
index 8f2f2f8d..4964d775 100644
--- a/app/helpers/call_events.py
+++ b/app/helpers/call_events.py
@@ -42,7 +42,6 @@
     MessageModel,
     PersonaEnum as MessagePersonaEnum,
     extract_message_style,
-    remove_message_action,
 )
 from app.models.next import NextModel
 from app.models.synthesis import SynthesisModel
@@ -169,8 +168,6 @@ async def on_call_disconnected(
 
 @tracer.start_as_current_span("on_audio_connected")
 async def on_audio_connected(  # noqa: PLR0913
-    audio_bits_per_sample: int,
-    audio_channels: int,
     audio_in: asyncio.Queue[bytes],
     audio_out: asyncio.Queue[bytes | bool],
     audio_sample_rate: int,
@@ -186,8 +183,6 @@ async def on_audio_connected(  # noqa: PLR0913
     Starts the real-time conversation with the LLM.
     """
     await load_llm_chat(
-        audio_bits_per_sample=audio_bits_per_sample,
-        audio_channels=audio_channels,
         audio_in=audio_in,
         audio_out=audio_out,
         audio_sample_rate=audio_sample_rate,
@@ -636,7 +631,7 @@ def _validate(req: str | None) -> tuple[bool, str | None, str | None]:
     )
 
     # Delete action and style from the message as they are in the history and LLM hallucinates them
-    _, content = extract_message_style(remove_message_action(content or ""))
+    _, content = extract_message_style(content or "")
 
     if not content:
         logger.warning("Error generating SMS report")
diff --git a/app/helpers/call_llm.py b/app/helpers/call_llm.py
index 9cc7a133..5199b787 100644
--- a/app/helpers/call_llm.py
+++ b/app/helpers/call_llm.py
@@ -10,14 +10,9 @@
 from azure.cognitiveservices.speech.audio import PushAudioInputStream
 from azure.communication.callautomation.aio import CallAutomationClient
 from openai import APIError
-from pydub import AudioSegment
-from pydub.effects import (
-    high_pass_filter,
-    low_pass_filter,
-)
-from webrtcvad import Vad
 
 from app.helpers.call_utils import (
+    EchoCancellationStream,
     handle_media,
     handle_realtime_tts,
     tts_sentence_split,
@@ -48,7 +43,6 @@
     StyleEnum as MessageStyleEnum,
     ToolModel as MessageToolModel,
     extract_message_style,
-    remove_message_action,
 )
 
 _db = CONFIG.database.instance()
@@ -56,9 +50,7 @@
 
 # TODO: Refacto, this function is too long
 @tracer.start_as_current_span("call_load_llm_chat")
-async def load_llm_chat(  # noqa: PLR0913
-    audio_bits_per_sample: int,
-    audio_channels: int,
+async def load_llm_chat(  # noqa: PLR0913, PLR0915
     audio_in: asyncio.Queue[bytes],
     audio_out: asyncio.Queue[bytes | bool],
     audio_sample_rate: int,
@@ -71,16 +63,56 @@ async def load_llm_chat(  # noqa: PLR0913
     # Init language recognition
     stt_buffer: list[str] = []  # Temporary buffer for recognition
     stt_complete_gate = asyncio.Event()  # Gate to wait for the recognition
+    aec = EchoCancellationStream(
+        sample_rate=audio_sample_rate,
+    )
+    audio_reference: asyncio.Queue[bytes] = asyncio.Queue()
 
-    def _stt_callback(text: str) -> None:
+    async def _send_in_to_aec() -> None:
         """
-        Store the recognition in the buffer.
+        Send input audio to the echo cancellation.
         """
-        # Skip if no text
-        if not text:
-            return
+        while True:
+            in_chunck = await audio_in.get()
+            audio_in.task_done()
+            await aec.push_input(in_chunck)
+
+    async def _send_out_to_aec() -> None:
+        """
+        Forward the TTS to the echo cancellation and output.
+        """
+        while True:
+            out_chunck = await audio_reference.get()
+            audio_reference.task_done()
+            await asyncio.gather(
+                # First, send the audio to the output
+                audio_out.put(out_chunck),
+                # Then, send the audio to the echo cancellation
+                aec.push_reference(out_chunck),
+            )
 
-        stt_buffer.append(text)
+    def _partial_stt_callback(text: str) -> None:
+        """
+        Store the partial recognition in the buffer.
+        """
+        # Init buffer if empty
+        if not stt_buffer:
+            stt_buffer.append("")
+        # Append the recognition
+        stt_buffer[-1] += text
+        logger.debug("Partial recognition: %s", stt_buffer)
+
+    def _complete_stt_callback(text: str) -> None:
+        """
+        Store the recognition in the buffer.
+        """
+        # Init buffer if empty
+        if not stt_buffer:
+            stt_buffer.append("")
+        # Store the recognition
+        stt_buffer[-1] = text
+        # Add a new buffer for the next partial recognition
+        stt_buffer.append("")
         logger.debug("Complete recognition: %s", stt_buffer)
 
         # Open the recognition gate
@@ -88,15 +120,14 @@ def _stt_callback(text: str) -> None:
 
     async with (
         use_stt_client(
-            audio_bits_per_sample=audio_bits_per_sample,
-            audio_channels=audio_channels,
             audio_sample_rate=audio_sample_rate,
             call=call,
-            callback=_stt_callback,
+            complete_callback=_complete_stt_callback,
+            partial_callback=_partial_stt_callback,
         ) as stt_stream,
         use_tts_client(
-            audio=audio_out,
             call=call,
+            out=audio_reference,
         ) as tts_client,
     ):
         # Build scheduler
@@ -121,32 +152,32 @@ async def _timeout_callback() -> None:
                 )
             )
 
-        async def _clear_audio_callback() -> None:
+        async def _stop_callback() -> None:
             """
             Triggered when the audio buffer needs to be cleared.
             """
+            # Close previous response now
+            if last_response:
+                await last_response.close(timeout=0)
+
             # Stop TTS, clear the buffer and send a stop signal
             tts_client.stop_speaking_async()
-            while not audio_out.empty():
-                audio_out.get_nowait()
-                audio_out.task_done()
-            await audio_out.put(False)
 
-            # Close the recognition gate
+            # Reset the recognition
+            stt_buffer.clear()
             stt_complete_gate.clear()
 
-            # Close previous response if any
-            if last_response:
-                await scheduler.spawn(last_response.close(timeout=0))
-
-            # Clear the recognition buffer
-            stt_buffer.clear()
+            # Send a stop signal
+            await audio_out.put(False)
 
         async def _commit_answer(tool_blacklist: set[str] | None = None) -> None:
             """
             Process the response.
             """
-            # Store recognition task
+            # Stop any previous response
+            await _stop_callback()
+
+            # Start chat task
             nonlocal last_response
             last_response = await scheduler.spawn(
                 _continue_chat(
@@ -160,21 +191,31 @@ async def _commit_answer(tool_blacklist: set[str] | None = None) -> None:
                 )
             )
 
-            # Wait for the response to be processed
+            # Wait for its response
             await last_response.wait()
 
-        async def _response_callback() -> None:
+        async def _response_callback(_retry: bool = False) -> None:
             """
             Triggered when the audio buffer needs to be processed.
+
+            If the recognition is empty, retry the recognition once. Otherwise, process the response.
             """
-            # Wait for the complete recognition
-            await stt_complete_gate.wait()
+            # Wait the complete recognition for 50ms maximum
+            try:
+                await asyncio.wait_for(stt_complete_gate.wait(), timeout=0.05)
+            except TimeoutError:
+                pass
 
             stt_text = " ".join(stt_buffer).strip()
 
-            # Skip if no partial recognition
+            # Ignore empty recognition
             if not stt_text:
-                return
+                # Skip if already retries
+                if _retry:
+                    return
+                # Retry recognition, maybe the user was too fast or the recognition is temporarly slow
+                await asyncio.sleep(0.2)
+                return await _response_callback(_retry=True)
 
             # Add it to the call history and update last interaction
             logger.info("Voice stored: %s", stt_buffer)
@@ -212,16 +253,21 @@ async def _response_callback() -> None:
                 {"end_call"},
             )
 
-        await _process_chat_audio(
-            bits_per_sample=audio_bits_per_sample,
-            call=call,
-            channels=audio_channels,
-            clear_audio_callback=_clear_audio_callback,
-            in_stream=audio_in,
-            out_stream=stt_stream,
-            response_callback=_response_callback,
-            sample_rate=audio_sample_rate,
-            timeout_callback=_timeout_callback,
+        await asyncio.gather(
+            # Start the echo cancellation
+            aec.process_stream(),
+            # Apply the echo cancellation
+            _send_in_to_aec(),
+            _send_out_to_aec(),
+            # Detect VAD
+            _process_audio_for_vad(
+                call=call,
+                stop_callback=_stop_callback,
+                echo_cancellation=aec,
+                out_stream=stt_stream,
+                response_callback=_response_callback,
+                timeout_callback=_timeout_callback,
+            ),
         )
 
 
@@ -454,7 +500,7 @@ async def _plugin_tts_callback(text: str) -> None:
 
     async def _content_callback(buffer: str) -> None:
         # Remove tool calls from buffer content and detect style
-        style, local_content = extract_message_style(remove_message_action(buffer))
+        style, local_content = extract_message_style(buffer)
         await tts_callback(local_content, style)
 
     # Build RAG
@@ -543,9 +589,7 @@ async def _content_callback(buffer: str) -> None:
     tool_calls = [tool_call for _, tool_call in tool_calls_buffer.items()]
 
     # Delete action and style from the message as they are in the history and LLM hallucinates them
-    last_style, content_full = extract_message_style(
-        remove_message_action(content_full)
-    )
+    last_style, content_full = extract_message_style(content_full)
 
     logger.debug("Completion response: %s", content_full)
     logger.debug("Completion tools: %s", tool_calls)
@@ -601,38 +645,41 @@ async def _content_callback(buffer: str) -> None:
 
 
 # TODO: Refacto and simplify
-async def _process_chat_audio(  # noqa: PLR0913
-    bits_per_sample: int,
+async def _process_audio_for_vad(  # noqa: PLR0913
     call: CallStateModel,
-    channels: int,
-    clear_audio_callback: Callable[[], Awaitable[None]],
-    in_stream: asyncio.Queue[bytes],
+    echo_cancellation: EchoCancellationStream,
     out_stream: PushAudioInputStream,
     response_callback: Callable[[], Awaitable[None]],
-    sample_rate: int,
+    stop_callback: Callable[[], Awaitable[None]],
     timeout_callback: Callable[[], Awaitable[None]],
 ) -> None:
-    clear_tts_task: asyncio.Task | None = None
+    """
+    Process voice activity and silence detection.
+
+    Follows the following steps:
+
+    - Detect voice activity and clear the TTS to let the user speak
+    - Wait for silence and trigger the chat
+    - Wait for longer silence and trigger the timeout
+    """
+    stop_task: asyncio.Task | None = None
     silence_task: asyncio.Task | None = None
-    vad = Vad(
-        # Aggressiveness mode (0, 1, 2, or 3)
-        # Sets the VAD operating mode. A more aggressive (higher mode) VAD is more restrictive in reporting speech. Put in other words the probability of being speech when the VAD returns 1 is increased with increasing mode. As a consequence also the missed detection rate goes up.
-        mode=3,
-    )
 
-    async def _silence_callback() -> None:
+    async def _wait_for_silence() -> None:
         """
-        Flush the audio buffer if no audio is detected for a while and trigger the timeout if required.
+        Run the chat after a silence.
+
+        If the silence is too long, run the timeout.
         """
         # Wait before flushing
-        nonlocal clear_tts_task
+        nonlocal stop_task
         timeout_ms = await vad_silence_timeout_ms()
         await asyncio.sleep(timeout_ms / 1000)
 
-        # Cancel the clear TTS task if any
-        if clear_tts_task:
-            clear_tts_task.cancel()
-            clear_tts_task = None
+        # Cancel the clear TTS task
+        if stop_task:
+            stop_task.cancel()
+            stop_task = None
 
         # Flush the audio buffer
         logger.debug("Flushing audio buffer after %i ms", timeout_ms)
@@ -664,11 +711,9 @@ async def _silence_callback() -> None:
             logger.info("Silence triggered after %i sec", timeout_sec)
             await timeout_callback()
 
-    async def _clear_tts_callback() -> None:
+    async def _wait_for_stop() -> None:
         """
-        Clear the TTS queue.
-
-        Start is the index of the buffer where the TTS was triggered.
+        Stop the TTS if user speaks for too long.
         """
         timeout_ms = await vad_cutoff_timeout_ms()
 
@@ -678,55 +723,31 @@ async def _clear_tts_callback() -> None:
         logger.debug("Canceling TTS after %i ms", timeout_ms)
 
         # Clear the queue
-        await clear_audio_callback()
+        await stop_callback()
 
-    # Consumes audio stream
     while True:
         # Wait for the next audio packet
-        in_chunck = await in_stream.get()
-
-        # Load audio
-        in_audio: AudioSegment = AudioSegment(
-            channels=channels,
-            data=in_chunck,
-            frame_rate=sample_rate,
-            sample_width=bits_per_sample // 8,
-        )
-
-        # Apply high-pass and low-pass filters in a simple attempt to reduce noise
-        in_audio = high_pass_filter(seg=in_audio, cutoff=85)
-        in_audio = low_pass_filter(seg=in_audio, cutoff=3000)
-
-        # Always add the audio to the buffer
-        assert isinstance(in_audio.raw_data, bytes)
-        out_stream.write(in_audio.raw_data)
+        out_chunck, is_speech = await echo_cancellation.pull_audio()
 
-        # Confirm ASAP that the event is processed
-        in_stream.task_done()
+        # Add audio to the buffer
+        out_stream.write(out_chunck)
 
-        # Use WebRTC VAD algorithm to detect voice
-        in_empty = False
-        if not vad.is_speech(
-            buf=in_audio.raw_data,
-            sample_rate=in_audio.frame_rate,
-        ):
-            in_empty = True
+        # If no speech, init the silence task
+        if not is_speech:
             # Start timeout if not already started
             if not silence_task:
-                silence_task = asyncio.create_task(_silence_callback())
-
-        if in_empty:
+                silence_task = asyncio.create_task(_wait_for_silence())
             # Continue to the next audio packet
             continue
 
-        # Voice detected, cancel the timeout if any
+        # Voice detected, cancel the timeout task
         if silence_task:
             silence_task.cancel()
             silence_task = None
 
         # Start the TTS clear task
-        if not clear_tts_task:
-            clear_tts_task = asyncio.create_task(_clear_tts_callback())
+        if not stop_task:
+            stop_task = asyncio.create_task(_wait_for_stop())
 
 
 def _tts_callback(
diff --git a/app/helpers/call_utils.py b/app/helpers/call_utils.py
index 766b5cef..67e0533f 100644
--- a/app/helpers/call_utils.py
+++ b/app/helpers/call_utils.py
@@ -5,11 +5,13 @@
 from contextlib import asynccontextmanager, contextmanager, suppress
 from enum import Enum
 
+import numpy as np
 from aiojobs import Job, Scheduler
 from azure.cognitiveservices.speech import (
     AudioConfig,
     SpeechConfig,
     SpeechRecognizer,
+    SpeechSynthesisOutputFormat,
     SpeechSynthesizer,
 )
 from azure.cognitiveservices.speech.audio import (
@@ -34,9 +36,11 @@
     CallConnectionClient,
 )
 from azure.core.exceptions import HttpResponseError, ResourceNotFoundError
+from noisereduce import reduce_noise
 
 from app.helpers.cache import async_lru_cache
 from app.helpers.config import CONFIG
+from app.helpers.features import vad_threshold
 from app.helpers.identity import token
 from app.helpers.logging import logger
 from app.models.call import CallStateModel
@@ -70,13 +74,24 @@ class TtsCallback(PushAudioOutputStreamCallback):
     Callback for Azure Speech Synthesizer to push audio data to a queue.
     """
 
-    def __init__(self, queue: asyncio.Queue[bytes | bool]):
+    def __init__(self, queue: asyncio.Queue[bytes]):
         self.queue = queue
 
     def write(self, audio_buffer: memoryview) -> int:
+        """
+        Write audio data to the queue.
+        """
         self.queue.put_nowait(audio_buffer.tobytes())
         return audio_buffer.nbytes
 
+    def close(self) -> None:
+        """
+        Close the callback.
+        """
+        while not self.queue.empty():
+            self.queue.get_nowait()
+            self.queue.task_done()
+
 
 class ContextEnum(str, Enum):
     """
@@ -523,11 +538,15 @@ async def _use_call_client(
 
 @asynccontextmanager
 async def use_tts_client(
-    audio: asyncio.Queue[bytes | bool],
     call: CallStateModel,
+    out: asyncio.Queue[bytes],
 ) -> AsyncGenerator[SpeechSynthesizer, None]:
     """
     Use a text-to-speech client for a call.
+
+    Output format is in PCM 16-bit, 16 kHz, 1 channel.
+
+    Yields a client to push audio data to the queue. Once the context is exited, the client will stop.
     """
     # Get AAD token
     aad_token = await (await token("https://cognitiveservices.azure.com/.default"))()
@@ -536,19 +555,21 @@ async def use_tts_client(
     # TODO: Use v2 endpoint (https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-lower-speech-synthesis-latency?pivots=programming-language-python#how-to-use-text-streaming) but seems compatible with AAD auth? Found nothing in the docs (https://github.com/Azure-Samples/cognitive-services-speech-sdk/blob/e392c9ca09d44ebd65081e7cb44593a2b16cd5a7/samples/python/web/avatar/app.py#L137).
     config = SpeechConfig(
         endpoint=f"wss://{CONFIG.cognitive_service.region}.tts.speech.microsoft.com/cognitiveservices/websocket/v1",
+        speech_recognition_language=call.lang.short_code,
     )
     config.authorization_token = (
         f"aad#{CONFIG.cognitive_service.resource_id}#{aad_token}"
     )
     config.speech_synthesis_voice_name = call.lang.voice
+    config.set_speech_synthesis_output_format(
+        SpeechSynthesisOutputFormat.Raw16Khz16BitMonoPcm
+    )
     if call.lang.custom_voice_endpoint_id:
         config.endpoint_id = call.lang.custom_voice_endpoint_id
     # TODO: How to close the client?
     client = SpeechSynthesizer(
         speech_config=config,
-        audio_config=AudioOutputConfig(
-            stream=PushAudioOutputStream(TtsCallback(audio))
-        ),
+        audio_config=AudioOutputConfig(stream=PushAudioOutputStream(TtsCallback(out))),
     )
 
     # Connect events
@@ -561,15 +582,16 @@ async def use_tts_client(
 
 @asynccontextmanager
 async def use_stt_client(
-    audio_bits_per_sample: int,
-    audio_channels: int,
     audio_sample_rate: int,
     call: CallStateModel,
-    callback: Callable[[str], None],
+    complete_callback: Callable[[str], None],
+    partial_callback: Callable[[str], None],
 ) -> AsyncGenerator[PushAudioInputStream, None]:
     """
     Use a speech-to-text client for a call.
 
+    Input format is in PCM 16-bit, 16 kHz, 1 channel.
+
     Yields a stream to push audio data to the client. Once the context is exited, the client will stop.
     """
     # Get AAD token
@@ -577,9 +599,10 @@ async def use_stt_client(
 
     # Create client
     stream = PushAudioInputStream(
+        # PCM 16-bit, 1 channel
         stream_format=AudioStreamFormat(
-            bits_per_sample=audio_bits_per_sample,
-            channels=audio_channels,
+            bits_per_sample=16,
+            channels=1,
             samples_per_second=audio_sample_rate,
         ),
     )
@@ -592,11 +615,18 @@ async def use_stt_client(
         ),
     )
 
-    # Connect events
-    client.recognized.connect(lambda e: callback(e.result.text))
+    # TSS events
+    client.recognized.connect(
+        lambda e: complete_callback(e.result.text) if e.result.text else None
+    )
+    client.recognizing.connect(
+        lambda e: partial_callback(e.result.text) if e.result.text else None
+    )
+
+    # Debugging events
+    client.canceled.connect(lambda event: logger.warning("STT cancelled: %s", event))
     client.session_started.connect(lambda _: logger.debug("STT started"))
     client.session_stopped.connect(lambda _: logger.debug("STT stopped"))
-    client.canceled.connect(lambda event: logger.warning("STT cancelled: %s", event))
 
     try:
         # Start STT
@@ -606,3 +636,184 @@ async def use_stt_client(
     finally:
         # Stop STT
         client.stop_continuous_recognition_async()
+
+
+class EchoCancellationStream:
+    """
+    Real-time audio stream with echo cancellation.
+
+    Input and output formats are in PCM 16-bit, 16 kHz, 1 channel.
+    """
+
+    _chunk_size: int
+    _input_queue: asyncio.Queue[bytes] = asyncio.Queue()
+    _output_queue: asyncio.Queue[tuple[bytes, bool]] = asyncio.Queue()
+    _packet_duration_ms: int
+    _packet_size: int
+    _reference_queue: asyncio.Queue[bytes] = asyncio.Queue()
+    _sample_rate: int
+
+    def __init__(
+        self,
+        sample_rate: int,
+        max_delay_ms: int = 200,
+        packet_duration_ms: int = 20,
+    ):
+        self._packet_duration_ms = packet_duration_ms
+        self._sample_rate = sample_rate
+
+        max_delay_samples = int(max_delay_ms / 1000 * self._sample_rate)
+        self._bot_voice_buffer = np.zeros(max_delay_samples, dtype=np.float32)
+
+        self._chunk_size = int(self._sample_rate * self._packet_duration_ms / 1000)
+        self._packet_size = self._chunk_size * 2  # Each sample is 2 bytes (PCM 16-bit)
+
+    def _pcm_to_float(self, pcm: bytes) -> np.ndarray:
+        """
+        Convert PCM 16-bit to float (-1.0 to 1.0).
+        """
+        return (
+            np.frombuffer(
+                buffer=pcm,
+                dtype=np.int16,
+            ).astype(np.float32)
+            / 32768.0
+        )
+
+    def _float_to_pcm(self, floats: np.ndarray) -> bytes:
+        """
+        Convert float (-1.0 to 1.0) to PCM 16-bit.
+        """
+        pcm = (floats * 32767).clip(-32768, 32767).astype(np.int16)
+        return pcm.tobytes()
+
+    def _update_input_buffer(self, voice: np.ndarray) -> None:
+        """
+        Update the rolling buffer for the input voice.
+        """
+        buffer_length = len(self._bot_voice_buffer)
+        reference_length = len(voice)
+
+        if reference_length >= buffer_length:
+            # If the reference is longer than the buffer, keep the most recent samples
+            self._bot_voice_buffer = voice[-buffer_length:]
+        else:
+            # Append new samples and keep the buffer size fixed
+            self._bot_voice_buffer = np.roll(self._bot_voice_buffer, -reference_length)
+            self._bot_voice_buffer[-reference_length:] = voice
+
+    async def _rms_speech_detection(self, voice: np.ndarray) -> bool:
+        """
+        Simple speech detection based on RMS (acoustic pressure).
+
+        Returns True if speech is detected, False otherwise.
+        """
+        # Calculate Root Mean Square (RMS)
+        rms = np.sqrt(np.mean(voice**2))
+        # Get VAD threshold, divide by 10 to more usability from user side, as RMS is in range 0-1 and a detection of 0.1 is a good maximum threshold
+        threshold = await vad_threshold() / 10
+        return rms >= threshold
+
+    async def _process_one(self, input_pcm: bytes) -> None:
+        """
+        Process one audio chunk with echo cancellation.
+        """
+        # Use silence as the reference if none is available
+        if self._reference_queue.empty():
+            reference_pcm = b"\x00" * self._packet_size
+        else:
+            reference_pcm = await self._reference_queue.get()
+            self._reference_queue.task_done()
+
+        # Convert PCM to float for processing
+        input_signal = self._pcm_to_float(input_pcm)
+        reference_signal = self._pcm_to_float(reference_pcm)
+
+        # Update the input buffer with the reference signal
+        self._update_input_buffer(reference_signal)
+
+        # Apply noise reduction
+        reduced_signal = reduce_noise(
+            # Input signal
+            clip_noise_stationary=False,
+            sr=self._sample_rate,
+            y=input_signal,
+            # Performance
+            n_fft=self._chunk_size,
+            # Since the reference signal is already noise-reduced, we can assume it's stationary
+            stationary=True,
+            y_noise=self._bot_voice_buffer,
+            # Output quality
+            prop_decrease=0.75,  # Reduce noise by 75%
+        )
+
+        # Perform VAD test
+        input_speaking = await self._rms_speech_detection(reduced_signal)
+
+        # Convert processed float signal back to PCM
+        processed_pcm = self._float_to_pcm(reduced_signal)
+
+        # Add processed PCM and metadata to the output queue
+        await self._output_queue.put((processed_pcm, input_speaking))
+
+    async def process_stream(self) -> None:
+        """
+        Process the audio stream in real-time.
+        """
+        async with Scheduler(
+            limit=5,  # Allow 5 concurrent tasks
+        ) as scheduler:
+            while True:
+                # Fetch input audio
+                input_pcm = await self._input_queue.get()
+                self._input_queue.task_done()
+
+                # Queue the processing
+                await scheduler.spawn(
+                    asyncio.wait_for(
+                        self._process_one(input_pcm),
+                        timeout=self._packet_duration_ms
+                        / 1000
+                        * 5,  # Allow temporary high latency
+                    )
+                )
+
+    async def push_input(self, audio_data: bytes) -> None:
+        """
+        Push PCM input audio into the input queue.
+        """
+        if len(audio_data) != self._packet_size:
+            raise ValueError(
+                f"Expected packet size {self._packet_size} bytes, got {len(audio_data)} bytes."
+            )
+        await self._input_queue.put(audio_data)
+
+    async def push_reference(self, audio_data: bytes) -> None:
+        """
+        Push PCM reference audio into the reference queue.
+
+        The reference audio is used for echo cancellation.
+        """
+        # Extract packets and pad them if necessary
+        buffer_pointer = 0
+        while buffer_pointer < len(audio_data):
+            chunk = audio_data[: self._packet_size].ljust(self._packet_size, b"\x00")
+            await self._reference_queue.put(chunk)
+            buffer_pointer += self._packet_size
+
+    async def pull_audio(self) -> tuple[bytes, bool]:
+        """
+        Pull processed PCM audio and metadata from the output queue.
+
+        Returns a tuple with the echo-cancelled PCM audio and a boolean flag indicating if the user was speaking.
+        """
+        # return await self._output_queue.get()
+        try:
+            return await asyncio.wait_for(
+                fut=self._output_queue.get(),
+                timeout=self._packet_duration_ms
+                / 1000
+                * 1.5,  # Allow temporary small latency
+            )
+        except TimeoutError:
+            return b"\x00" * self._packet_size, False  # Silence PCM chunk and no speech
diff --git a/app/helpers/features.py b/app/helpers/features.py
index cd9cd3a1..392f7736 100644
--- a/app/helpers/features.py
+++ b/app/helpers/features.py
@@ -18,42 +18,103 @@
 
 
 async def answer_hard_timeout_sec() -> int:
-    return await _get(key="answer_hard_timeout_sec", type_res=int) or 180
+    return await _default(
+        default=180,
+        key="answer_hard_timeout_sec",
+        type_res=int,
+    )
 
 
 async def answer_soft_timeout_sec() -> int:
-    return await _get(key="answer_soft_timeout_sec", type_res=int) or 120
+    return await _default(
+        default=120,
+        key="answer_soft_timeout_sec",
+        type_res=int,
+    )
 
 
 async def callback_timeout_hour() -> int:
-    return await _get(key="callback_timeout_hour", type_res=int) or 24
+    return await _default(
+        default=24,
+        key="callback_timeout_hour",
+        type_res=int,
+    )
 
 
 async def phone_silence_timeout_sec() -> int:
-    return await _get(key="phone_silence_timeout_sec", type_res=int) or 20
+    return await _default(
+        default=20,
+        key="phone_silence_timeout_sec",
+        type_res=int,
+    )
+
+
+async def vad_threshold() -> float:
+    return await _default(
+        default=0.5,
+        key="vad_threshold",
+        type_res=float,
+    )
 
 
 async def vad_silence_timeout_ms() -> int:
-    return await _get(key="vad_silence_timeout_ms", type_res=int) or 400
+    return await _default(
+        default=400,
+        key="vad_silence_timeout_ms",
+        type_res=int,
+    )
 
 
 async def vad_cutoff_timeout_ms() -> int:
-    return await _get(key="vad_cutoff_timeout_ms", type_res=int) or 600
+    return await _default(
+        default=600,
+        key="vad_cutoff_timeout_ms",
+        type_res=int,
+    )
 
 
 async def recording_enabled() -> bool:
-    return await _get(key="recording_enabled", type_res=bool) or False
+    return await _default(
+        default=False,
+        key="recording_enabled",
+        type_res=bool,
+    )
 
 
 async def slow_llm_for_chat() -> bool:
-    return await _get(key="slow_llm_for_chat", type_res=bool) or True
+    return await _default(
+        default=True,
+        key="slow_llm_for_chat",
+        type_res=bool,
+    )
 
 
 async def recognition_retry_max() -> int:
-    return await _get(key="recognition_retry_max", type_res=int) or 3
+    return await _default(
+        default=3,
+        key="recognition_retry_max",
+        type_res=int,
+    )
 
 
-async def _get(key: str, type_res: type[T]) -> T | None:
+async def _default(
+    default: T,
+    key: str,
+    type_res: type[T],
+) -> T:
+    """
+    Get a setting from the App Configuration service with a default value.
+    """
+    return (await _get(key=key, type_res=type_res)) or default
+
+
+async def _get(
+    key: str,
+    type_res: type[T],
+) -> T | None:
+    """
+    Get a setting from the App Configuration service.
+    """
     # Try cache
     cache_key = _cache_key(key)
     cached = await _cache.get(cache_key)
@@ -99,10 +160,18 @@ async def _use_client() -> AzureAppConfigurationClient:
 
 
 def _cache_key(key: str) -> str:
+    """
+    Generate a cache key for a setting.
+    """
     return f"{__name__}-{key}"
 
 
 def _parse(value: str, type_res: type[T]) -> T | None:
+    """
+    Parse a setting value to a type.
+
+    Supported types: bool, int, float, str.
+    """
     with suppress(ValueError):
         if type_res is bool:
             return cast(T, value.lower() == "true")
diff --git a/app/main.py b/app/main.py
index fd3b2b87..0ffdaf4f 100644
--- a/app/main.py
+++ b/app/main.py
@@ -612,6 +612,7 @@ async def _send_audio() -> None:
         with suppress(WebSocketDisconnect):
             while True:
                 audio_data = await audio_out.get()
+                audio_out.task_done()
                 # Send audio
                 if isinstance(audio_data, bytes):
                     await websocket.send_json(
@@ -630,7 +631,6 @@ async def _send_audio() -> None:
                             "stopAudio": {},
                         }
                     )
-                audio_out.task_done()
 
     async with get_scheduler() as scheduler:
         await asyncio.gather(
@@ -641,8 +641,6 @@ async def _send_audio() -> None:
             # Process audio
             # TODO: Dynamically set the audio format
             on_audio_connected(
-                audio_bits_per_sample=16,
-                audio_channels=1,
                 audio_in=audio_in,
                 audio_out=audio_out,
                 audio_sample_rate=16000,
diff --git a/app/models/message.py b/app/models/message.py
index 09eab8de..842a0c87 100644
--- a/app/models/message.py
+++ b/app/models/message.py
@@ -1,11 +1,7 @@
-import json
 import re
 from datetime import UTC, datetime
 from enum import Enum
-from inspect import getmembers, isfunction
-from typing import Any
 
-from json_repair import repair_json
 from openai.types.chat import (
     ChatCompletionAssistantMessageParam,
     ChatCompletionMessageToolCallParam,
@@ -15,8 +11,6 @@
 from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall
 from pydantic import BaseModel, Field, field_validator
 
-from app.helpers.monitoring import tracer
-
 _FUNC_NAME_SANITIZER_R = r"[^a-zA-Z0-9_-]"
 _MESSAGE_ACTION_R = r"(?:action=*([a-z_]*))? *(.*)"
 _MESSAGE_STYLE_R = r"(?:style=*([a-z_]*))? *(.*)"
@@ -169,9 +163,11 @@ def to_openai(
         return res
 
 
-def remove_message_action(text: str) -> str:
+def _filter_action(text: str) -> str:
     """
-    Remove action from content. AI often adds it by mistake event if explicitly asked not to.
+    Remove action from content.
+
+    AI often adds it by mistake event if explicitly asked not to.
 
     Example:
     - Input: "action=talk Hello!"
@@ -188,6 +184,19 @@ def remove_message_action(text: str) -> str:
         return text
 
 
+def _filter_content(text: str) -> str:
+    """
+    Remove content from text.
+
+    AI often adds it by mistake event if explicitly asked not to.
+
+    Example:
+    - Input: "content=Hello!"
+    - Output: "Hello!"
+    """
+    return text.replace("content=", "")
+
+
 def extract_message_style(text: str) -> tuple[StyleEnum, str]:
     """
     Detect the style of a message and extract it from the text.
@@ -196,6 +205,11 @@ def extract_message_style(text: str) -> tuple[StyleEnum, str]:
     - Input: "style=cheerful Hello!"
     - Output: (StyleEnum.CHEERFUL, "Hello!")
     """
+    # Apply hallucination filters
+    text = _filter_action(text)
+    text = _filter_content(text)
+
+    # Extract style
     default_style = StyleEnum.NONE
     res = re.match(_MESSAGE_STYLE_R, text)
     if not res:
@@ -205,6 +219,7 @@ def extract_message_style(text: str) -> tuple[StyleEnum, str]:
             StyleEnum(res.group(1)),  # style
             (res.group(2) or ""),  # content
         )
+
     # Regex failed, return original text
     except ValueError:
         return default_style, text
diff --git a/app/persistence/ai_search.py b/app/persistence/ai_search.py
index a5610bbe..5719c3c7 100644
--- a/app/persistence/ai_search.py
+++ b/app/persistence/ai_search.py
@@ -165,7 +165,8 @@ async def training_search_all(
         except ResourceNotFoundError:
             logger.warning('AI Search index "%s" not found', self._config.index)
         except HttpResponseError as e:
-            if "too many requests" in e.message.lower():
+            message = e.message.lower()
+            if "too many requests" in message or "exceed the limits" in message:
                 raise TooManyRequests()
             logger.error("Error requesting AI Search: %s", e)
         except ServiceRequestError as e:
diff --git a/cicd/bicep/app.bicep b/cicd/bicep/app.bicep
index 37c7e42a..16e60ebe 100644
--- a/cicd/bicep/app.bicep
+++ b/cicd/bicep/app.bicep
@@ -909,6 +909,7 @@ resource configValues 'Microsoft.AppConfiguration/configurationStores/keyValues@
     slow_llm_for_chat: false
     vad_cutoff_timeout_ms: 600
     vad_silence_timeout_ms: 400
+    vad_threshold: '0.5'
   }): {
     parent: configStore
     name: item.key
diff --git a/pyproject.toml b/pyproject.toml
index bd1d2a57..7fd75e1b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -26,6 +26,7 @@ dependencies = [
   "jinja2~=3.1",  # Template engine, used for prompts and web views
   "json-repair~=0.30",  # Repair JSON files from LLM
   "mistune~=3.0",  # Markdown parser for web views
+  "noisereduce~=3.0", # Noise reduction
   "openai~=1.52",  # OpenAI client
   "opentelemetry-instrumentation-aiohttp-client~=0.0a0",  # OpenTelemetry instrumentation for aiohttp client
   "opentelemetry-instrumentation-httpx~=0.0a0",  # OpenTelemetry instrumentation for HTTPX
@@ -36,7 +37,6 @@ dependencies = [
   "pydantic-extra-types~=2.9",  # Extra types for Pydantic
   "pydantic-settings~=2.6",  # Application configuration management with Pydantic
   "pydantic[email]~=2.9",  # Data serialization and validation, plus email validation
-  "pydub~=0.25",  # Audio processing with FFmpeg
   "pyjwt~=2.9",  # Secure inbound calls from Communication Services
   "python-dotenv~=1.0",  # Load environment variables from .env file
   "python-multipart==0.*",  # Form parsing
@@ -49,7 +49,6 @@ dependencies = [
   "twilio~=9.3",  # Twilio SDK, used for SMS
   "typing-extensions~=4.12",  # Typing extensions for Python 3.6+
   "uvicorn[standard]~=0.32",  # Application middleware
-  "webrtcvad~=2.0",  # Voice activity detection
 ]
 
 [project.optional-dependencies]
diff --git a/uv.lock b/uv.lock
index f26868e3..75352b2f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -471,6 +471,7 @@ dependencies = [
     { name = "jinja2" },
     { name = "json-repair" },
     { name = "mistune" },
+    { name = "noisereduce" },
     { name = "openai" },
     { name = "opentelemetry-instrumentation-aiohttp-client" },
     { name = "opentelemetry-instrumentation-httpx" },
@@ -481,7 +482,6 @@ dependencies = [
     { name = "pydantic", extra = ["email"] },
     { name = "pydantic-extra-types" },
     { name = "pydantic-settings" },
-    { name = "pydub" },
     { name = "pyjwt" },
     { name = "python-dotenv" },
     { name = "python-multipart" },
@@ -494,7 +494,6 @@ dependencies = [
     { name = "twilio" },
     { name = "typing-extensions" },
     { name = "uvicorn", extra = ["standard"] },
-    { name = "webrtcvad" },
 ]
 
 [package.optional-dependencies]
@@ -534,6 +533,7 @@ requires-dist = [
     { name = "jinja2", specifier = "~=3.1" },
     { name = "json-repair", specifier = "~=0.30" },
     { name = "mistune", specifier = "~=3.0" },
+    { name = "noisereduce", specifier = "~=3.0" },
     { name = "openai", specifier = "~=1.52" },
     { name = "opentelemetry-instrumentation-aiohttp-client", specifier = "~=0.0a0" },
     { name = "opentelemetry-instrumentation-httpx", specifier = "~=0.0a0" },
@@ -544,7 +544,6 @@ requires-dist = [
     { name = "pydantic", extras = ["email"], specifier = "~=2.9" },
     { name = "pydantic-extra-types", specifier = "~=2.9" },
     { name = "pydantic-settings", specifier = "~=2.6" },
-    { name = "pydub", specifier = "~=0.25" },
     { name = "pyjwt", specifier = "~=2.9" },
     { name = "pyright", marker = "extra == 'dev'", specifier = "~=1.1" },
     { name = "pytest", marker = "extra == 'dev'", specifier = "~=8.3" },
@@ -564,7 +563,6 @@ requires-dist = [
     { name = "twilio", specifier = "~=9.3" },
     { name = "typing-extensions", specifier = "~=4.12" },
     { name = "uvicorn", extras = ["standard"], specifier = "~=0.32" },
-    { name = "webrtcvad", specifier = "~=2.0" },
 ]
 
 [[package]]
@@ -669,6 +667,47 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335 },
 ]
 
+[[package]]
+name = "contourpy"
+version = "1.3.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/25/c2/fc7193cc5383637ff390a712e88e4ded0452c9fbcf84abe3de5ea3df1866/contourpy-1.3.1.tar.gz", hash = "sha256:dfd97abd83335045a913e3bcc4a09c0ceadbe66580cf573fe961f4a825efa699", size = 13465753 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/37/6b/175f60227d3e7f5f1549fcb374592be311293132207e451c3d7c654c25fb/contourpy-1.3.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:0ffa84be8e0bd33410b17189f7164c3589c229ce5db85798076a3fa136d0e509", size = 271494 },
+    { url = "https://files.pythonhosted.org/packages/6b/6a/7833cfae2c1e63d1d8875a50fd23371394f540ce809d7383550681a1fa64/contourpy-1.3.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:805617228ba7e2cbbfb6c503858e626ab528ac2a32a04a2fe88ffaf6b02c32bc", size = 255444 },
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 [[package]]
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     { url = "https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78", size = 11774 },
 ]
 
-[[package]]
-name = "webrtcvad"
-version = "2.0.10"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/89/34/e2de2d97f3288512b9ea56f92e7452f8207eb5a0096500badf9dfd48f5e6/webrtcvad-2.0.10.tar.gz", hash = "sha256:f1bed2fb25b63fb7b1a55d64090c993c9c9167b28485ae0bcdd81cf6ede96aea", size = 66156 }
-
 [[package]]
 name = "websockets"
 version = "14.1"