Injecting External Bot TTS Audio into Genesys Cloud Calls via AudioHook

How-To-Articles
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Injecting External Bot TTS Audio into Genesys Cloud Calls via AudioHook

What This Guide Covers

This guide details the configuration of Genesys Cloud AudioHook to stream call audio to an external service, generate Text-to-Speech (TTS) audio from that service, and inject the resulting PCM audio payload back into the active call stream. You will configure the AudioHook stream parameters, structure the webhook response payloads for real-time audio injection, manage sample rate alignment, and implement a chunking strategy to prevent buffer underruns and latency artifacts.

Prerequisites, Roles & Licensing

  • Licensing Tier: Genesys Cloud CX3 or higher, or CX1/CX2 with the AudioHook add-on license. AudioHook is not included in base CX1/CX2 bundles.
  • Permissions:
    • Telephony > AudioHook > Edit to create and modify AudioHook definitions.
    • Architect > Flow > Edit to add AudioHook blocks to IVR or routing flows.
    • Telephony > Trunk > View to verify codec support if injecting into SIP trunks.
  • OAuth Scopes: If managing via API, audiohook:control and flow:edit.
  • External Dependencies:
    • A TTS engine capable of streaming output or generating audio chunks on demand.
    • A webhook endpoint with sub-50ms response time for the control plane.
    • Network path allowing Genesys Cloud egress to your webhook and ingress from your webhook to Genesys.

The Implementation Deep-Dive

1. AudioHook Configuration and Stream Parameters

The AudioHook definition dictates how Genesys Cloud slices the audio stream before sending it to your webhook. Misconfiguration here causes sample rate drift, audio distortion, or excessive latency.

Navigate to Admin > Telephony > AudioHook and create a new definition.

Critical Configuration Keys:

  • Sample Rate: Set to 8000 Hz for PSTN/SIP calls or 16000 Hz for digital-only channels. This value must match the output sample rate of your TTS engine exactly. If your TTS engine outputs 24000 Hz, you must perform real-time downsampling to the configured rate before injection. Genesys Cloud does not resample injected audio.
  • Chunk Size: Set to 20 ms. This is the standard balance between latency and overhead. Smaller chunks (10 ms) reduce latency but increase HTTP request volume and CPU overhead. Larger chunks (40 ms) increase latency and make barge-in detection slower.
  • Send Audio: Enable Send Audio to receive inbound speech from the participant.
  • Receive Audio: Enable Receive Audio. This is mandatory for TTS injection. If this is disabled, the webhook can analyze audio but cannot inject audio back into the stream.
  • Latency Budget: Configure the Timeout value. Set this to 100 ms. If your webhook exceeds this time, Genesys Cloud assumes the service is down and injects silence or terminates the hook depending on the flow configuration.

The Trap: Setting Chunk Size to 40 ms or higher while expecting natural conversation flow. A 40 ms chunk size introduces at least 40 ms of buffering delay per round trip. When combined with network latency and TTS generation time, the total delay exceeds 300 ms, causing participants to talk over the bot or perceive the bot as “lagging.” Always use 20 ms chunks for conversational TTS injection.

The Trap: Mismatched Sample Rates. If AudioHook is configured for 8000 Hz and you inject 16000 Hz PCM data, the audio plays back at half speed with a lowered pitch. If you inject 8000 Hz data into a 16000 Hz hook, the audio plays back at double speed with a chipmunk pitch. Validate the sampleRate in the AudioHook config matches the byte rate of your TTS output payload.

2. Architect Flow and Block Configuration

The AudioHook block in Architect controls the lifecycle of the injection. You must configure the block to handle the audio stream and manage barge-in events.

Add the AudioHook block to your flow. Connect the Start node to the AudioHook block.

Block Configuration:

  • AudioHook Definition: Select the definition created in Step 1.
  • Audio Hook URL: Enter your webhook endpoint. This URL receives the audio chunks and returns the TTS audio.
  • Timeout: Set to 5000 ms (5 seconds). This is the maximum duration the AudioHook block remains active before forcing a transition. For long conversations, use a loop or a state machine pattern rather than a single long timeout.
  • On Timeout: Route to a cleanup block or a human transfer.
  • Barge-in Handling: Enable Allow Barge-in. If your TTS injection is active and the participant speaks, Genesys Cloud sends a DTMF or silence interruption signal. Your webhook must detect this and stop sending TTS audio immediately.

Architect Expression for Session State:
Use an expression to pass a unique session identifier to the webhook. This allows your backend to maintain the TTS buffer state per call.

// Architect Expression: Set Session ID in Headers
{
  "headers": {
    "X-Genesys-Session": "${interaction.id}",
    "X-Genesys-Participant": "${participant.id}"
  }
}

The Trap: Forgetting to handle the control field in the Architect block settings. If you do not configure the block to expect a control response, Genesys Cloud may default to continue or stop based on HTTP status codes alone. Explicitly configure the block to parse the control field from the JSON response to manage flow transitions.

3. Webhook Response Structure and PCM Injection

The webhook response is the mechanism for injecting TTS. Genesys Cloud expects a specific JSON structure containing base64-encoded PCM audio data.

HTTP Response Requirements:

  • Method: POST.
  • Status Code: 200 OK. Any non-200 status causes Genesys to inject silence or error handling.
  • Content-Type: application/json.
  • Response Time: Must be under the configured timeout (typically 100 ms).

JSON Payload Structure:
The response body must contain the audio field with base64-encoded signed 16-bit PCM data. The control field dictates the hook lifecycle.

{
  "audio": "BASE64_ENCODED_SIGNED_16BIT_PCM_DATA",
  "control": "continue",
  "dtmf": ""
}

Field Definitions:

  • audio: Base64 string of PCM audio. The length must match the chunk size. For 20 ms at 8000 Hz, 16-bit mono, the raw byte length is 8000 * 2 * 0.02 = 320 bytes. The base64 string length will be approximately 320 * 4 / 3 = 426 characters. If the base64 string length deviates significantly, Genesys Cloud may drop the chunk.
  • control:
    • continue: Keep the AudioHook active and wait for the next chunk request.
    • stop: End the AudioHook session and proceed to the next block in Architect.
    • barge: Signal that the participant has interrupted (rarely used by webhook; usually detected by Genesys).
  • dtmf: Optional. Inject DTMF tones if required by legacy systems.

Code Example: Python Flask Webhook Handler:

import base64
import json
from flask import Flask, request, jsonify

app = Flask(__name__)

# Simulated TTS engine that returns PCM bytes
def generate_tts_chunk(text_segment):
    # Returns signed 16-bit PCM bytes matching AudioHook sample rate
    # Implementation depends on your TTS provider
    return pcm_bytes

@app.route('/audiohook/webhook', methods=['POST'])
def audiohook_handler():
    try:
        # 1. Extract session ID for state management
        session_id = request.headers.get('X-Genesys-Session')
        
        # 2. Retrieve TTS audio from buffer or generate new chunk
        # Your backend must maintain a queue of TTS chunks per session
        pcm_chunk = tts_manager.get_next_chunk(session_id)
        
        # 3. Encode to Base64
        # Ensure no newlines or padding issues
        audio_b64 = base64.b64encode(pcm_chunk).decode('utf-8')
        
        # 4. Determine control state
        control = "continue"
        if tts_manager.is_buffer_empty(session_id):
            control = "stop"
            
        # 5. Return response within latency budget
        return jsonify({
            "audio": audio_b64,
            "control": control
        }), 200
        
    except Exception as e:
        # Return silence on error to prevent call drop
        # 320 bytes of silence for 8000Hz 20ms chunk
        silence_b64 = base64.b64encode(b'\x00' * 320).decode('utf-8')
        return jsonify({
            "audio": silence_b64,
            "control": "continue"
        }), 200

The Trap: Injecting WAV headers or MP3 data. The audio field must contain raw PCM only. If you include a WAV header (44 bytes), Genesys Cloud interprets the header bytes as audio samples, resulting in loud clicks or static. Always strip container headers before base64 encoding.

The Trap: Variable chunk sizes. If you send a 20 ms chunk in one response and a 40 ms chunk in the next, Genesys Cloud may buffer incorrectly, causing audio pops or desync. Maintain strict adherence to the chunk size defined in the AudioHook configuration. If your TTS engine produces variable lengths, pad or trim the PCM data to match the expected byte count exactly.

4. TTS Generation Pipeline and Buffer Management

Real-time TTS injection requires a streaming architecture. You cannot wait for the full sentence to generate before responding. You must implement a lookahead buffer to decouple TTS generation latency from AudioHook response latency.

Pipeline Architecture:

  1. Ingestion: Receive audio chunk from Genesys.
  2. STT/Logic: Transcribe and determine response text asynchronously.
  3. TTS Generation: Generate TTS audio in background threads.
  4. Chunk Queue: Push TTS audio into a per-session queue of 20 ms chunks.
  5. Response: Pop the next chunk from the queue and respond to Genesys immediately.

Buffer Management Logic:

  • Pre-generation: As soon as the bot decides on a response text, trigger TTS generation for the entire sentence. Push chunks into the queue as they become available.
  • Latency Masking: If the first chunk takes 150 ms to generate, the queue will be empty for 150 ms. Genesys Cloud will request chunks every 20 ms. You must return silence chunks until the first TTS chunk is ready. This hides the generation latency from the participant, though it introduces a pause. To avoid pauses, use SSML pauses or fast-fill strategies where the bot speaks a filler phrase while generating the main response.
  • Barge-in Handling: Monitor the participant audio stream. If speech is detected, flush the TTS queue and send silence. This prevents the bot from continuing to speak while the participant interrupts.

The Trap: Synchronous TTS generation. If your webhook calls the TTS engine synchronously and waits for the result before returning, the response time will exceed 100 ms. Genesys Cloud will timeout and inject silence. Always generate TTS asynchronously and maintain a pre-filled buffer. The webhook response must only perform a queue pop and encode operation, which should take less than 5 ms.

The Trap: Buffer Underruns during High Load. If multiple calls trigger TTS simultaneously, your backend may struggle to keep up. If the queue empties, you must return silence immediately. If you return an error or delay, Genesys Cloud may drop the AudioHook session. Implement a circuit breaker pattern: if the TTS service is overloaded, return silence and log a warning, rather than blocking the webhook response.

Validation, Edge Cases & Troubleshooting

Edge Case 1: Sample Rate Mismatch and Audio Distortion

  • Failure Condition: Injected audio plays back with distorted pitch, speed, or static clicks.
  • Root Cause: The TTS engine output sample rate does not match the AudioHook configuration. For example, AudioHook is 8000 Hz, but TTS outputs 16000 Hz.
  • Solution: Verify the sampleRate in the AudioHook definition. Update the TTS engine configuration to output the exact same sample rate. If the TTS engine cannot change output rate, implement a real-time resampling step (e.g., using sox or pydub) before injection. Validate by injecting a known sine wave tone and analyzing the frequency in Wireshark or a packet capture tool.

Edge Case 2: TTS Latency and Buffer Underruns

  • Failure Condition: The bot speaks with noticeable gaps, stuttering, or silence between words.
  • Root Cause: The TTS generation pipeline cannot produce chunks fast enough to fill the queue. The webhook returns silence chunks because the queue is empty.
  • Solution: Profile the TTS generation latency. If the latency exceeds 200 ms, optimize the TTS model or switch to a streaming TTS provider. Implement a larger lookahead buffer by generating TTS for multiple sentences in advance. Monitor the queue depth in your backend logs; if the depth drops below 3 chunks, trigger an alert. Consider using a faster TTS model for the first few words to reduce initial latency.

Edge Case 3: Barge-In Detection During Audio Injection

  • Failure Condition: The participant interrupts the bot, but the bot continues speaking, causing audio overlap.
  • Root Cause: The webhook does not detect speech in the inbound audio stream and continues pushing TTS chunks.
  • Solution: Implement Voice Activity Detection (VAD) on the inbound audio chunks. Calculate the RMS energy of the PCM data. If the energy exceeds a threshold (e.g., -30 dBFS) for more than 2 consecutive chunks, flag barge-in. When barge-in is detected, flush the TTS queue and return silence chunks. Update the control field to stop if the interruption signifies the end of the bot’s turn. Reference the Speech Analytics integration patterns for advanced VAD algorithms.

Edge Case 4: Base64 Padding and Chunk Size Drift

  • Failure Condition: Audio plays correctly for a few seconds, then Genesys Cloud terminates the AudioHook with a “Malformed Response” error.
  • Root Cause: The base64 string length varies due to padding or incorrect byte counting. Genesys Cloud expects a fixed byte length per chunk.
  • Solution: Ensure the PCM chunk length is exactly sampleRate * 2 * chunkDurationMs / 1000. For 8000 Hz and 20 ms, this is 320 bytes. Use base64.b64encode without line breaks. Validate the base64 string length is consistent across all responses. If the TTS engine produces a chunk that is 318 bytes, pad with 2 bytes of silence (\x00\x00) to reach 320 bytes. Never send a chunk shorter than the expected length.

Official References