Azure AI Speech (Cognitive Services)
Azure AI Speech is Azure's Cognitive Services text-to-speech API, separate from Azure OpenAI. It provides high-quality neural voices with broader language support and advanced speech customization.
When to use this vs Azure OpenAI TTS:
- Azure AI Speech - More languages, neural voices, SSML support, speech customization
- Azure OpenAI TTS - OpenAI models, integrated with Azure OpenAI services
Overview
| Property | Details | 
|---|---|
| Description | Azure AI Speech is Azure's Cognitive Services text-to-speech API, separate from Azure OpenAI. It provides high-quality neural voices with broader language support and advanced speech customization. | 
| Provider Route on LiteLLM | azure/speech/ | 
Quick Start
LiteLLM SDK
from litellm import speech
from pathlib import Path
import os
os.environ["AZURE_TTS_API_KEY"] = "your-cognitive-services-key"
speech_file_path = Path(__file__).parent / "speech.mp3"
response = speech(
    model="azure/speech/azure-tts",
    voice="alloy",
    input="Hello, this is Azure AI Speech",
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
)
response.stream_to_file(speech_file_path)
LiteLLM Proxy
model_list:
  - model_name: azure-speech
    litellm_params:
      model: azure/speech/azure-tts
      api_base: https://eastus.tts.speech.microsoft.com
      api_key: os.environ/AZURE_TTS_API_KEY
Setup
- Create an Azure Cognitive Services resource in the Azure Portal
- Get your API key from the resource
- Note your region (e.g., eastus,westus,westeurope)
- Use the regional endpoint: https://{region}.tts.speech.microsoft.com
Cost Tracking (Pricing)
LiteLLM automatically tracks costs for Azure AI Speech based on the number of characters processed.
Available Models
| Model | Voice Type | Cost per 1M Characters | 
|---|---|---|
| azure/speech/azure-tts | Neural | $15 | 
| azure/speech/azure-tts-hd | Neural HD | $30 | 
How Costs are Calculated
Azure AI Speech charges based on the number of characters in your input text. LiteLLM automatically:
- Counts the number of characters in your inputparameter
- Calculates the cost based on the model pricing
- Returns the cost in the response object
from litellm import speech
response = speech(
    model="azure/speech/azure-tts",
    voice="alloy",
    input="Hello, this is a test message",
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
)
# Access the calculated cost
cost = response._hidden_params.get("response_cost")
print(f"Request cost: ${cost}")
Verify Azure Pricing
To check the latest Azure AI Speech pricing:
- Visit the Azure Pricing Calculator
- Set Service to "AI Services"
- Set API to "Azure AI Speech"
- Select Text to Speech and your region
- View the current pricing per million characters
Note: Pricing may vary by region and Azure subscription type.
Voice Mapping
LiteLLM automatically maps OpenAI voice names to Azure Neural voices:
| OpenAI Voice | Azure Neural Voice | Description | 
|---|---|---|
| alloy | en-US-JennyNeural | Neutral and balanced | 
| echo | en-US-GuyNeural | Warm and upbeat | 
| fable | en-GB-RyanNeural | Expressive and dramatic | 
| onyx | en-US-DavisNeural | Deep and authoritative | 
| nova | en-US-AmberNeural | Friendly and conversational | 
| shimmer | en-US-AriaNeural | Bright and cheerful | 
Supported Parameters
response = speech(
    model="azure/speech/azure-tts",
    voice="alloy",                    # Required: Voice selection
    input="text to convert",          # Required: Input text
    speed=1.0,                        # Optional: 0.25 to 4.0 (default: 1.0)
    response_format="mp3",            # Optional: mp3, opus, wav, pcm
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key="your-key",
)
Response Formats
| Format | Azure Output Format | Sample Rate | 
|---|---|---|
| mp3 | audio-24khz-48kbitrate-mono-mp3 | 24kHz | 
| opus | ogg-48khz-16bit-mono-opus | 48kHz | 
| wav | riff-24khz-16bit-mono-pcm | 24kHz | 
| pcm | raw-24khz-16bit-mono-pcm | 24kHz | 
Sending Azure-Specific Params
Azure AI Speech supports advanced SSML features through optional parameters:
- style: Speaking style (e.g., "cheerful", "sad", "angry", "whispering")
- styledegree: Style intensity (0.01 to 2)
- role: Voice role (e.g., "Girl", "Boy", "SeniorFemale", "SeniorMale")
- lang: Language code for multilingual voices (e.g., "es-ES", "fr-FR", "hi-IN")
LiteLLM SDK
Custom Azure Voice
from litellm import speech
response = speech(
    model="azure/speech/azure-tts",
    voice="en-US-AndrewNeural",       # Use Azure voice directly
    input="Hello, this is a test",
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
    response_format="mp3"
)
response.stream_to_file("speech.mp3")
Speaking Style
from litellm import speech
response = speech(
    model="azure/speech/azure-tts",
    voice="en-US-JennyNeural",        # Must be a voice that supports styles
    input="Who are you? What is chicken dinner?",
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
    style="whispering",               # Azure-specific: cheerful, sad, angry, whispering, etc.
)
response.stream_to_file("speech.mp3")
Style with Degree and Role
from litellm import speech
response = speech(
    model="azure/speech/azure-tts",
    voice="en-US-AriaNeural",
    input="Good morning! How are you today?",
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
    style="cheerful",                 # Azure-specific: Speaking style
    styledegree="2",                  # Azure-specific: 0.01 to 2 (intensity)
    role="SeniorFemale",              # Azure-specific: Girl, Boy, SeniorFemale, etc.
)
response.stream_to_file("speech.mp3")
Language Override for Multilingual Voices
from litellm import speech
response = speech(
    model="azure/speech/azure-tts",
    voice="en-US-AvaMultilingualNeural",  # Multilingual voice
    input="आप कौन हैं? चिकन डिनर क्या है?",  # Hindi text
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
    lang="hi-IN",                         # Azure-specific: Override language
)
response.stream_to_file("speech.mp3")
LiteLLM AI Gateway (CURL)
First, ensure you have set up your proxy config as shown in the LiteLLM Proxy setup above.
Using the model name from your config:
model_list:
  - model_name: azure-speech  # This is what you'll use in your API calls
    litellm_params:
      model: azure/speech/azure-tts
      api_base: https://eastus.tts.speech.microsoft.com
      api_key: os.environ/AZURE_TTS_API_KEY
Custom Azure Voice
curl http://0.0.0.0:4000/v1/audio/speech \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "azure-speech",
    "voice": "en-US-AndrewNeural",
    "input": "Hello, this is a test"
  }' \
  --output speech.mp3
Speaking Style
curl http://0.0.0.0:4000/v1/audio/speech \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "azure-speech",
    "input": "Who are you? What is chicken dinner?",
    "voice": "en-US-JennyNeural",
    "style": "whispering"
  }' \
  --output speech.mp3
Style with Degree and Role
curl http://0.0.0.0:4000/v1/audio/speech \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "azure-speech",
    "voice": "en-US-AriaNeural",
    "input": "Good morning! How are you today?",
    "style": "cheerful",
    "styledegree": "2",
    "role": "SeniorFemale"
  }' \
  --output speech.mp3
Language Override
curl http://0.0.0.0:4000/v1/audio/speech \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "azure-speech",
    "input": "आप कौन हैं? चिकन डिनर क्या है?",
    "voice": "en-US-AvaMultilingualNeural",
    "lang": "hi-IN"
  }' \
  --output speech.mp3
Azure-Specific Parameters Reference
| Parameter | Description | Example Values | Notes | 
|---|---|---|---|
| style | Speaking style | cheerful,sad,angry,excited,friendly,hopeful,shouting,terrified,unfriendly,whispering | Only supported by certain voices. See Azure voice styles documentation | 
| styledegree | Style intensity | 0.01to2 | Higher values = more intense. Default is 1 | 
| role | Voice role | Girl,Boy,YoungAdultFemale,YoungAdultMale,OlderAdultFemale,OlderAdultMale,SeniorFemale,SeniorMale | Only supported by certain voices | 
| lang | Language code | es-ES,fr-FR,de-DE,hi-IN, etc. | For multilingual voices. Overrides the default language | 
Async Support
import asyncio
from litellm import aspeech
from pathlib import Path
async def generate_speech():
    response = await aspeech(
        model="azure/speech/azure-tts",
        voice="alloy",
        input="Hello from async",
        api_base="https://eastus.tts.speech.microsoft.com",
        api_key=os.environ["AZURE_TTS_API_KEY"],
    )
    
    speech_file_path = Path(__file__).parent / "speech.mp3"
    response.stream_to_file(speech_file_path)
asyncio.run(generate_speech())
Regional Endpoints
Replace {region} with your Azure resource region:
- US East: https://eastus.tts.speech.microsoft.com
- US West: https://westus.tts.speech.microsoft.com
- Europe West: https://westeurope.tts.speech.microsoft.com
- Asia Southeast: https://southeastasia.tts.speech.microsoft.com
Advanced Features
Custom Neural Voices
You can use any Azure Neural voice by passing the full voice name:
response = speech(
    model="azure/speech/azure-tts",
    voice="en-US-AriaNeural",  # Direct Azure voice name
    input="Using a specific neural voice",
    api_base="https://eastus.tts.speech.microsoft.com",
    api_key=os.environ["AZURE_TTS_API_KEY"],
)
Browse available voices in the Azure Speech Gallery.
Error Handling
from litellm import speech
from litellm.exceptions import APIError
try:
    response = speech(
        model="azure/speech/azure-tts",
        voice="alloy",
        input="Test message",
        api_base="https://eastus.tts.speech.microsoft.com",
        api_key=os.environ["AZURE_TTS_API_KEY"],
    )
except APIError as e:
    print(f"Azure Speech error: {e}")