AI Voice System Configuration & Fine-Tuning
Budget: ₹12,500 – ₹37,500 INR
We are building a production-grade AI Calling Agent using a 2-VM architecture:
VM-1 → Telephony, SIP trunk, media handling, STT & TTS (THIS TASK)
VM-2 → AI Brain (LLM + Vector DB) – handled separately
This project is strictly limited to VM-1.
The freelancer will set up telephony, real-time audio processing, STT/TTS, API connectivity, and perform full fine-tuning so that live calls sound natural, stable, and low-latency.
Scope of Work (VM-1 Only)
VM & Network Setup
OS: Ubuntu (preferred) on Proxmox
Configure:
Public interface → SIP + RTP
Private interface → AI Brain API
Optimize OS for:
Low-latency audio
High concurrent calls
Firewall configuration:
SIP (TLS)
RTP port range
Internal API access only
SIP Trunk & Telephony Configuration
Configure SIP Trunk (provider details will be shared)
SIP over TLS preferred
Handle:
Incoming & outgoing calls
NAT traversal
DTMF
Call start / end events
Codec setup:
Opus (primary)
G.711 (fallback)
Telephony stack:
FreeSWITCH / Kamailio / OpenSIPS (freelancer must justify choice)
Media & Call Flow Handling
Handle RTP audio streams in real time
Call flow:
Receive caller audio
Stream audio to STT
Receive AI response
Convert to TTS
Play back audio to caller
Support:
Voice Activity Detection (VAD)
Silence detection
Caller barge-in (interrupt AI speech)
STT (Speech-to-Text) Integration
Integrate real-time STT
Audio streaming in chunks
Handle:
Partial transcripts
Final transcripts
Tune for:
Indian accents
Background noise
Fast & slow speakers
Ensure no loss of first/last words
TTS (Text-to-Speech) Integration
Integrate low-latency TTS
Telephony-optimized voices
Tune:
Speed
Pitch
Volume normalization
Playback must:
Start quickly
Sound natural
Stop immediately on barge-in
API Layer for AI Brain Connectivity
Expose secure APIs for VM-2:
Send transcript + call context
Receive response text / intent / action
API requirements:
HTTPS
Token-based authentication
Low-latency response handling
Provide API documentation:
Endpoints
Payload structure
Timeout & retry logic
Fine-Tuning & Optimization (MANDATORY)
A. Telephony & Audio Fine-Tuning
Optimize:
SIP timers
RTP jitter buffers
Packet loss handling
Eliminate:
Audio clipping
Echo
One-way audio
Tune Opus bitrate & fallback behavior
B. STT Accuracy Fine-Tuning
Tune:
Sample rate (16 kHz mono preferred)
Chunk size
Silence thresholds
Reduce:
False silence detection
Missed or cut words
Validate with real call recordings
C. TTS Naturalness Fine-Tuning
Optimize:
Pause timing
Natural speech gaps
Voice clarity over phone lines
Ensure human-like response timing
D. End-to-End Latency Optimization
Optimize full loop:
Caller → STT → AI Brain → TTS → Playback
Remove bottlenecks in:
Audio pipeline
Network calls
API responses
Goal: near-human conversational delay
E. Failure & Fallback Handling
Graceful handling for:
AI Brain timeout
STT/TTS failure
Play fallback audio instead of dropping calls
Ensure VM-1 never crashes due to external API delays
Real-World Call Testing (REQUIRED)
Freelancer must test & fine-tune for:
Silent caller
Continuous speech
Caller interrupting AI
Background noise
Long calls (10–15 minutes)
Multiple back-to-back calls
Deliverables
Fully working VM-1
SIP trunk tested with live calls
End-to-end demo call
API documentation
Fine-tuning parameters & recommendations
Deployment & restart guide
Source/config files ownership transferred
Acceptance Criteria
Calls connect reliably
Audio is clear & natural
No noticeable lag in AI responses
STT accuracy acceptable for Indian callers
TTS stops instantly on barge-in
System remains stable under repeated calls
Required Skills
SIP / RTP / VoIP
FreeSWITCH / Kamailio / OpenSIPS
Real-time audio streaming
STT & TTS systems
Linux server hardening
API design
AI voice bot experience (strong plus)
Out of Scope
Frontend or UI
LLM prompt engineering
Vector DB setup
AI Brain logic (VM-2)
Proposal Must Include
Proposed telephony stack and reason
Similar AI voice/IVR projects done
Estimated timeline
Assumptions & risks
Estimated Timeline
Setup & integration: 7–10 days
Fine-tuning & testing: 5–7 days
VM-1 → Telephony, SIP trunk, media handling, STT & TTS (THIS TASK)
VM-2 → AI Brain (LLM + Vector DB) – handled separately
This project is strictly limited to VM-1.
The freelancer will set up telephony, real-time audio processing, STT/TTS, API connectivity, and perform full fine-tuning so that live calls sound natural, stable, and low-latency.
Scope of Work (VM-1 Only)
VM & Network Setup
OS: Ubuntu (preferred) on Proxmox
Configure:
Public interface → SIP + RTP
Private interface → AI Brain API
Optimize OS for:
Low-latency audio
High concurrent calls
Firewall configuration:
SIP (TLS)
RTP port range
Internal API access only
SIP Trunk & Telephony Configuration
Configure SIP Trunk (provider details will be shared)
SIP over TLS preferred
Handle:
Incoming & outgoing calls
NAT traversal
DTMF
Call start / end events
Codec setup:
Opus (primary)
G.711 (fallback)
Telephony stack:
FreeSWITCH / Kamailio / OpenSIPS (freelancer must justify choice)
Media & Call Flow Handling
Handle RTP audio streams in real time
Call flow:
Receive caller audio
Stream audio to STT
Receive AI response
Convert to TTS
Play back audio to caller
Support:
Voice Activity Detection (VAD)
Silence detection
Caller barge-in (interrupt AI speech)
STT (Speech-to-Text) Integration
Integrate real-time STT
Audio streaming in chunks
Handle:
Partial transcripts
Final transcripts
Tune for:
Indian accents
Background noise
Fast & slow speakers
Ensure no loss of first/last words
TTS (Text-to-Speech) Integration
Integrate low-latency TTS
Telephony-optimized voices
Tune:
Speed
Pitch
Volume normalization
Playback must:
Start quickly
Sound natural
Stop immediately on barge-in
API Layer for AI Brain Connectivity
Expose secure APIs for VM-2:
Send transcript + call context
Receive response text / intent / action
API requirements:
HTTPS
Token-based authentication
Low-latency response handling
Provide API documentation:
Endpoints
Payload structure
Timeout & retry logic
Fine-Tuning & Optimization (MANDATORY)
A. Telephony & Audio Fine-Tuning
Optimize:
SIP timers
RTP jitter buffers
Packet loss handling
Eliminate:
Audio clipping
Echo
One-way audio
Tune Opus bitrate & fallback behavior
B. STT Accuracy Fine-Tuning
Tune:
Sample rate (16 kHz mono preferred)
Chunk size
Silence thresholds
Reduce:
False silence detection
Missed or cut words
Validate with real call recordings
C. TTS Naturalness Fine-Tuning
Optimize:
Pause timing
Natural speech gaps
Voice clarity over phone lines
Ensure human-like response timing
D. End-to-End Latency Optimization
Optimize full loop:
Caller → STT → AI Brain → TTS → Playback
Remove bottlenecks in:
Audio pipeline
Network calls
API responses
Goal: near-human conversational delay
E. Failure & Fallback Handling
Graceful handling for:
AI Brain timeout
STT/TTS failure
Play fallback audio instead of dropping calls
Ensure VM-1 never crashes due to external API delays
Real-World Call Testing (REQUIRED)
Freelancer must test & fine-tune for:
Silent caller
Continuous speech
Caller interrupting AI
Background noise
Long calls (10–15 minutes)
Multiple back-to-back calls
Deliverables
Fully working VM-1
SIP trunk tested with live calls
End-to-end demo call
API documentation
Fine-tuning parameters & recommendations
Deployment & restart guide
Source/config files ownership transferred
Acceptance Criteria
Calls connect reliably
Audio is clear & natural
No noticeable lag in AI responses
STT accuracy acceptable for Indian callers
TTS stops instantly on barge-in
System remains stable under repeated calls
Required Skills
SIP / RTP / VoIP
FreeSWITCH / Kamailio / OpenSIPS
Real-time audio streaming
STT & TTS systems
Linux server hardening
API design
AI voice bot experience (strong plus)
Out of Scope
Frontend or UI
LLM prompt engineering
Vector DB setup
AI Brain logic (VM-2)
Proposal Must Include
Proposed telephony stack and reason
Similar AI voice/IVR projects done
Estimated timeline
Assumptions & risks
Estimated Timeline
Setup & integration: 7–10 days
Fine-tuning & testing: 5–7 days