Vapi's Accent and Noise Handling

100+ Language Support

Vapi integrates with providers covering:

• 97+ languages through OpenAI Whisper
• 142 languages through TTS providers
• Automatic language detection
• Mid-conversation language switching

Proprietary Endpointing Model

Challenge: Knowing when speaker finished vs natural pause Accent impact: Pause length varies across cultures and accents Solution: Vapi's endpointing model trained on multicultural conversation patterns Result: Conversations flow naturally without premature cutoff or awkward delays

Provider Flexibility

Multi-provider deployment: Route different languages to optimal providers Example: Use Whisper for Mandarin (superior accuracy), Deepgram for English (lower latency) A/B testing: Compare provider performance on your actual user population Dynamic routing: Switch providers based on detected language and accent

Built-in Acoustic Enhancement

Noise suppression: Automatic background noise reduction Echo cancellation: Eliminate acoustic echo without user action Volume normalization: Consistent audio levels across varied devices Quality monitoring: Real-time audio quality scoring with degradation alerts