516 lines
11 KiB
Markdown
516 lines
11 KiB
Markdown
# Provider Comparison Guide
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This guide compares different providers for transcription, LLM, and TTS services to help you choose the best option for your voice AI engine.
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## Transcription Providers
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### Deepgram
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**Strengths:**
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- ✅ Fastest transcription speed (< 300ms latency)
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- ✅ Excellent streaming support
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- ✅ High accuracy (95%+ on clear audio)
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- ✅ Good pricing ($0.0043/minute)
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- ✅ Nova-2 model optimized for real-time
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- ✅ Excellent documentation
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**Weaknesses:**
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- ❌ Less accurate with heavy accents
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- ❌ Smaller company (potential reliability concerns)
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**Best For:**
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- Real-time voice conversations
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- Low-latency applications
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- English-language applications
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- Startups and small businesses
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**Configuration:**
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```python
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{
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"transcriberProvider": "deepgram",
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"deepgramApiKey": "your-api-key",
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"deepgramModel": "nova-2",
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"language": "en-US"
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}
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```
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---
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### AssemblyAI
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**Strengths:**
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- ✅ Very high accuracy (96%+ on clear audio)
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- ✅ Excellent with accents and dialects
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- ✅ Good speaker diarization
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- ✅ Competitive pricing ($0.00025/second)
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- ✅ Strong customer support
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**Weaknesses:**
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- ❌ Slightly higher latency than Deepgram
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- ❌ Streaming support is newer
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**Best For:**
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- Applications requiring highest accuracy
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- Multi-speaker scenarios
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- Diverse user base with accents
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- Enterprise applications
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**Configuration:**
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```python
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{
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"transcriberProvider": "assemblyai",
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"assemblyaiApiKey": "your-api-key",
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"language": "en"
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}
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```
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---
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### Azure Speech
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**Strengths:**
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- ✅ Enterprise-grade reliability
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- ✅ Excellent multi-language support (100+ languages)
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- ✅ Strong security and compliance
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- ✅ Integration with Azure ecosystem
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- ✅ Custom model training available
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**Weaknesses:**
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- ❌ Higher cost ($1/hour)
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- ❌ More complex setup
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- ❌ Slower than specialized providers
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**Best For:**
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- Enterprise applications
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- Multi-language requirements
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- Azure-based infrastructure
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- Compliance-sensitive applications
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**Configuration:**
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```python
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{
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"transcriberProvider": "azure",
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"azureSpeechKey": "your-key",
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"azureSpeechRegion": "eastus",
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"language": "en-US"
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}
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```
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---
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### Google Cloud Speech
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**Strengths:**
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- ✅ Excellent multi-language support (125+ languages)
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- ✅ Good accuracy
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- ✅ Integration with Google Cloud
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- ✅ Automatic punctuation
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- ✅ Speaker diarization
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**Weaknesses:**
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- ❌ Higher latency for streaming
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- ❌ Complex pricing model
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- ❌ Requires Google Cloud account
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**Best For:**
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- Multi-language applications
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- Google Cloud infrastructure
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- Applications needing speaker diarization
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**Configuration:**
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```python
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{
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"transcriberProvider": "google",
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"googleCredentials": "path/to/credentials.json",
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"language": "en-US"
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}
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```
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---
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## LLM Providers
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### OpenAI (GPT-4, GPT-3.5)
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**Strengths:**
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- ✅ Highest quality responses
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- ✅ Excellent instruction following
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- ✅ Fast streaming
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- ✅ Large context window (128k for GPT-4)
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- ✅ Best-in-class reasoning
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**Weaknesses:**
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- ❌ Higher cost ($0.01-0.03/1k tokens)
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- ❌ Rate limits can be restrictive
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- ❌ No free tier
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**Best For:**
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- High-quality conversational AI
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- Complex reasoning tasks
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- Production applications
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- Enterprise use cases
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**Configuration:**
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```python
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{
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"llmProvider": "openai",
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"openaiApiKey": "your-api-key",
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"openaiModel": "gpt-4-turbo",
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"prompt": "You are a helpful AI assistant."
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}
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```
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**Pricing:**
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- GPT-4 Turbo: $0.01/1k input tokens, $0.03/1k output tokens
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- GPT-3.5 Turbo: $0.0005/1k input tokens, $0.0015/1k output tokens
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---
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### Google Gemini
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**Strengths:**
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- ✅ Excellent cost-effectiveness (free tier available)
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- ✅ Multimodal capabilities
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- ✅ Good streaming support
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- ✅ Large context window (1M tokens for Pro)
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- ✅ Fast response times
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**Weaknesses:**
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- ❌ Slightly lower quality than GPT-4
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- ❌ Less predictable behavior
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- ❌ Newer, less battle-tested
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**Best For:**
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- Cost-sensitive applications
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- Multimodal applications
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- Startups and prototypes
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- High-volume applications
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**Configuration:**
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```python
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{
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"llmProvider": "gemini",
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"geminiApiKey": "your-api-key",
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"geminiModel": "gemini-pro",
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"prompt": "You are a helpful AI assistant."
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}
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```
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**Pricing:**
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- Gemini Pro: Free up to 60 requests/minute
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- Gemini Pro (paid): $0.00025/1k input tokens, $0.0005/1k output tokens
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---
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### Anthropic Claude
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**Strengths:**
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- ✅ Excellent safety and alignment
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- ✅ Very long context window (200k tokens)
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- ✅ High-quality responses
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- ✅ Good at following complex instructions
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- ✅ Strong reasoning capabilities
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**Weaknesses:**
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- ❌ Higher cost than Gemini
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- ❌ Slower streaming than OpenAI
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- ❌ More conservative responses
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**Best For:**
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- Safety-critical applications
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- Long-context applications
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- Nuanced conversations
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- Enterprise applications
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**Configuration:**
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```python
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{
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"llmProvider": "claude",
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"claudeApiKey": "your-api-key",
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"claudeModel": "claude-3-opus",
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"prompt": "You are a helpful AI assistant."
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}
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```
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**Pricing:**
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- Claude 3 Opus: $0.015/1k input tokens, $0.075/1k output tokens
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- Claude 3 Sonnet: $0.003/1k input tokens, $0.015/1k output tokens
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---
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## TTS Providers
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### ElevenLabs
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**Strengths:**
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- ✅ Most natural-sounding voices
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- ✅ Excellent emotional range
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- ✅ Voice cloning capabilities
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- ✅ Good streaming support
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- ✅ Multiple languages
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**Weaknesses:**
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- ❌ Higher cost ($0.30/1k characters)
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- ❌ Rate limits on lower tiers
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- ❌ Occasional pronunciation errors
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**Best For:**
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- Premium voice experiences
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- Customer-facing applications
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- Voice cloning needs
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- High-quality audio requirements
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**Configuration:**
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```python
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{
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"voiceProvider": "elevenlabs",
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"elevenlabsApiKey": "your-api-key",
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"elevenlabsVoiceId": "voice-id",
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"elevenlabsModel": "eleven_monolingual_v1"
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}
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```
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**Pricing:**
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- Free: 10k characters/month
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- Starter: $5/month, 30k characters
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- Creator: $22/month, 100k characters
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---
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### Azure TTS
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**Strengths:**
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- ✅ Enterprise-grade reliability
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- ✅ Many languages (100+)
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- ✅ Neural voices available
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- ✅ SSML support for fine control
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- ✅ Good pricing ($4/1M characters)
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**Weaknesses:**
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- ❌ Less natural than ElevenLabs
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- ❌ More complex setup
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- ❌ Requires Azure account
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**Best For:**
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- Enterprise applications
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- Multi-language requirements
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- Azure-based infrastructure
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- Cost-sensitive high-volume applications
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**Configuration:**
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```python
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{
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"voiceProvider": "azure",
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"azureSpeechKey": "your-key",
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"azureSpeechRegion": "eastus",
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"azureVoiceName": "en-US-JennyNeural"
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}
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```
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**Pricing:**
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- Neural voices: $16/1M characters
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- Standard voices: $4/1M characters
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---
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### Google Cloud TTS
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**Strengths:**
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- ✅ Good quality neural voices
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- ✅ Many languages (40+)
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- ✅ WaveNet voices available
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- ✅ Competitive pricing ($4/1M characters)
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- ✅ SSML support
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**Weaknesses:**
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- ❌ Less natural than ElevenLabs
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- ❌ Requires Google Cloud account
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- ❌ Complex setup
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**Best For:**
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- Multi-language applications
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- Google Cloud infrastructure
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- Cost-effective neural voices
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**Configuration:**
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```python
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{
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"voiceProvider": "google",
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"googleCredentials": "path/to/credentials.json",
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"googleVoiceName": "en-US-Neural2-F"
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}
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```
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**Pricing:**
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- WaveNet voices: $16/1M characters
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- Neural2 voices: $16/1M characters
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- Standard voices: $4/1M characters
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---
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### Amazon Polly
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**Strengths:**
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- ✅ AWS integration
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- ✅ Good pricing ($4/1M characters)
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- ✅ Neural voices available
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- ✅ SSML support
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- ✅ Reliable service
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**Weaknesses:**
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- ❌ Less natural than ElevenLabs
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- ❌ Fewer voice options
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- ❌ Requires AWS account
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**Best For:**
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- AWS-based infrastructure
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- Cost-effective neural voices
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- Enterprise applications
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**Configuration:**
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```python
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{
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"voiceProvider": "polly",
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"awsAccessKey": "your-access-key",
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"awsSecretKey": "your-secret-key",
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"awsRegion": "us-east-1",
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"pollyVoiceId": "Joanna"
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}
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```
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**Pricing:**
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- Neural voices: $16/1M characters
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- Standard voices: $4/1M characters
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---
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### Play.ht
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**Strengths:**
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- ✅ Voice cloning capabilities
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- ✅ Natural-sounding voices
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- ✅ Good streaming support
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- ✅ Easy to use API
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- ✅ Multiple languages
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**Weaknesses:**
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- ❌ Higher cost than cloud providers
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- ❌ Smaller company
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- ❌ Less documentation
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**Best For:**
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- Voice cloning applications
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- Premium voice experiences
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- Startups and small businesses
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**Configuration:**
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```python
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{
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"voiceProvider": "playht",
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"playhtApiKey": "your-api-key",
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"playhtUserId": "your-user-id",
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"playhtVoiceId": "voice-id"
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}
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```
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**Pricing:**
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- Free: 2.5k characters
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- Creator: $31/month, 50k characters
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- Pro: $79/month, 150k characters
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---
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## Recommended Combinations
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### Budget-Conscious Startup
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```python
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{
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"transcriberProvider": "deepgram", # Fast and affordable
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"llmProvider": "gemini", # Free tier available
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"voiceProvider": "google" # Cost-effective neural voices
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}
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```
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**Estimated cost:** ~$0.01 per minute of conversation
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### Premium Experience
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```python
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{
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"transcriberProvider": "assemblyai", # Highest accuracy
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"llmProvider": "openai", # Best quality responses
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"voiceProvider": "elevenlabs" # Most natural voices
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}
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```
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**Estimated cost:** ~$0.05 per minute of conversation
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---
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### Enterprise Application
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```python
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{
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"transcriberProvider": "azure", # Enterprise reliability
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"llmProvider": "openai", # Best quality
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"voiceProvider": "azure" # Enterprise reliability
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}
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```
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**Estimated cost:** ~$0.03 per minute of conversation
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---
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### Multi-Language Application
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```python
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{
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"transcriberProvider": "google", # 125+ languages
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"llmProvider": "gemini", # Good multi-language support
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"voiceProvider": "google" # 40+ languages
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}
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```
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**Estimated cost:** ~$0.02 per minute of conversation
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---
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## Decision Matrix
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| Priority | Transcriber | LLM | TTS |
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|----------|-------------|-----|-----|
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| **Lowest Cost** | Deepgram | Gemini | Google |
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| **Highest Quality** | AssemblyAI | OpenAI | ElevenLabs |
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| **Fastest Speed** | Deepgram | OpenAI | ElevenLabs |
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| **Enterprise** | Azure | OpenAI | Azure |
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| **Multi-Language** | Google | Gemini | Google |
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| **Voice Cloning** | N/A | N/A | ElevenLabs/Play.ht |
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---
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## Testing Recommendations
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Before committing to providers, test with your specific use case:
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1. **Create test conversations** with representative audio
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2. **Measure latency** end-to-end
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3. **Evaluate quality** with real users
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4. **Calculate costs** based on expected volume
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5. **Test edge cases** (accents, background noise, interrupts)
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---
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## Switching Providers
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The multi-provider factory pattern makes switching easy:
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```python
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# Just change the configuration
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config = {
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"transcriberProvider": "deepgram", # Change to "assemblyai"
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"llmProvider": "gemini", # Change to "openai"
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"voiceProvider": "google" # Change to "elevenlabs"
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}
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# No code changes needed!
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factory = VoiceComponentFactory()
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transcriber = factory.create_transcriber(config)
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agent = factory.create_agent(config)
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synthesizer = factory.create_synthesizer(config)
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```
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