--- title: "Azure AI Speech（Cognitive Services）" url: "/docs/providers/azure_ai_speech" canonical_url: "https://docs.litellm.ai/docs/providers/azure_ai_speech" type: "docs" last_updated: "2026-10-08" related: - "/docs/providers/azure_document_intelligence" - "/docs/providers/azure_ai_img" --- # Azure AI Speech（Cognitive Services） > Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt Azure AI Speech 是 Azure 的 Cognitive Services 文字轉語音 API，獨立於 Azure OpenAI。它提供高品質神經語音，支援更多語言，並具備進階語音自訂功能。 **何時使用此服務而非 Azure OpenAI TTS：** - **Azure AI Speech** - 更多語言、神經語音、SSML 支援、語音自訂 - **Azure OpenAI TTS** - OpenAI 模型，與 Azure OpenAI 服務整合 ## 概觀 {#overview} | 屬性 | 詳細資訊 | |-------|-------| | 說明 | Azure AI Speech 是 Azure 的 Cognitive Services 文字轉語音 API，獨立於 Azure OpenAI。它提供高品質神經語音，支援更多語言，並具備進階語音自訂功能。 | | LiteLLM 上的提供者路由 | `azure/speech/` | ## 快速開始 {#quick-start} **LiteLLM SDK** ```python showLineNumbers title="SDK Usage" 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** ```yaml showLineNumbers title="proxy_config.yaml" 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 ``` ## 設定 {#setup} 1. 在 [Azure Portal](https://portal.azure.com) 中建立 Azure Cognitive Services 資源 2. 從該資源取得您的 API 金鑰 3. 記下您的區域（例如，`eastus`、`westus`、`westeurope`） 4. 使用區域端點：`https://{region}.tts.speech.microsoft.com` ## 成本追蹤（定價） {#cost-tracking-pricing} LiteLLM 會根據處理的字元數，自動追蹤 Azure AI Speech 的成本。 ### 可用模型 {#available-models} | 模型 | 語音類型 | 每 1M 字元成本 | |-------|-----------|----------------------| | `azure/speech/azure-tts` | Neural | $15 | | `azure/speech/azure-tts-hd` | Neural HD | $30 | ### 成本如何計算 {#how-costs-are-calculated} Azure AI Speech 會根據您輸入文字中的字元數計費。LiteLLM 會自動： - 計算您 `input` 參數中的字元數 - 根據模型定價計算成本 - 在回應物件中傳回成本 ```python showLineNumbers title="View Request Cost" 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}") ``` ### 驗證 Azure 定價 {#verify-azure-pricing} 若要查看最新的 Azure AI Speech 定價： 1. 造訪 [Azure 定價計算機](https://azure.microsoft.com/en-us/pricing/calculator/) 2. 將 **Service** 設為 "AI Services" 3. 將 **API** 設為 "Azure AI Speech" 4. 選擇 **Text to Speech** 與您的區域 5. 查看每百萬字元的目前定價 **注意：** 定價可能因區域與 Azure 訂用帳戶類型而異。 ## 語音對應 {#voice-mapping} LiteLLM 會自動將 OpenAI 語音名稱對應至 Azure Neural 語音： | OpenAI 語音 | Azure Neural 語音 | 說明 | |-------------|-------------------|-------------| | `alloy` | en-US-JennyNeural | 中性且平衡 | | `echo` | en-US-GuyNeural | 溫暖且活潑 | | `fable` | en-GB-RyanNeural | 富表現力且戲劇化 | | `onyx` | en-US-DavisNeural | 聲音低沉且具權威感 | | `nova` | en-US-AmberNeural | 親切且具對話感 | | `shimmer` | en-US-AriaNeural | 明亮且愉快 | ## 支援的參數 {#supported-parameters} ```python showLineNumbers title="All 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", ) ``` ### 回應格式 {#response-formats} | 格式 | Azure 輸出格式 | 取樣率 | |--------|-------------------|-------------| | `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 | ## 傳遞原始 SSML {#passing-raw-ssml} LiteLLM 會自動偵測您的 `input` 是否包含 SSML（透過檢查 `` 標籤），並在不做任何轉換的情況下將其傳遞給 Azure。這讓您能完整控制語音合成。 **何時使用原始 SSML：** - 搭配多語言語音使用 `` 元素來翻譯文字（例如，英文文字 → 西班牙語語音） - 具有多個語音或韻律變化的複雜 SSML 結構 - 對發音、停頓、強調及其他語音特徵進行精細控制 ### LiteLLM SDK {#litellm-sdk} ```python showLineNumbers title="Raw SSML for Multilingual Translation" from litellm import speech # Use element to convert English text to Spanish speech # The element forces the output language regardless of input text language language_code = "es-ES" text = "Hello, how are you today?" # English text voice = "en-US-AvaMultilingualNeural" ssml = f""" {text} """ response = speech( model="azure/speech/azure-tts", voice=voice, input=ssml, # LiteLLM auto-detects SSML and sends as-is api_base="https://eastus.tts.speech.microsoft.com", api_key=os.environ["AZURE_TTS_API_KEY"], ) response.stream_to_file("speech.mp3") ``` ```python showLineNumbers title="Raw SSML with Complex Features" from litellm import speech # Complex SSML with multiple prosody adjustments ssml = """ Welcome to our service! How can I help you today? """ response = speech( model="azure/speech/azure-tts", voice="en-US-JennyNeural", input=ssml, # LiteLLM detects and passes through unchanged api_base="https://eastus.tts.speech.microsoft.com", api_key=os.environ["AZURE_TTS_API_KEY"], ) response.stream_to_file("speech.mp3") ``` ### LiteLLM Proxy {#litellm-proxy} ```bash curl http://0.0.0.0:4000/v1/audio/speech \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "azure-speech", "voice": "en-US-AvaMultilingualNeural", "input": "Hello, how are you today?" }' \ --output speech.mp3 ``` ## 傳送 Azure 特定參數 {#sending-azure-specific-params} Azure AI Speech 透過可選參數支援進階 SSML 功能： - `style`：說話風格（例如，「cheerful」、「sad」、「angry」、「whispering」） - `styledegree`：風格強度（0.01 到 2） - `role`：語音角色（例如，「Girl」、「Boy」、「SeniorFemale」、「SeniorMale」） - `lang`：多語言語音的語言代碼（例如，「es-ES」、「fr-FR」、「hi-IN」） ### **LiteLLM SDK** {#litellm-sdk-1} #### 自訂 Azure 語音 {#custom-azure-voice} ```python showLineNumbers title="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") ``` #### 說話風格 {#speaking-style} ```python showLineNumbers title="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") ``` #### 風格、程度與角色 {#style-with-degree-and-role} ```python showLineNumbers title="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") ``` #### 多語言語音的語言覆寫 {#language-override-for-multilingual-voices} ```python showLineNumbers title="Language Override" 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)** {#litellm-ai-gateway-curl} 首先，請確保您已依照上方的 [LiteLLM Proxy 設定](#quick-start) 完成 proxy 設定。 **使用您設定檔中的模型名稱：** ```yaml 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 ``` #### 自訂 Azure 語音 {#custom-azure-voice-1} ```bash curl http://0.0.0.0:4000/v1/audio/speech \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "azure-speech", "voice": "en-US-AndrewNeural", "input": "Hello, this is a test" }' \ --output speech.mp3 ``` #### 說話風格 {#speaking-style-1} ```bash curl http://0.0.0.0:4000/v1/audio/speech \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -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 ``` #### 風格、程度與角色 {#style-with-degree-and-role-1} ```bash curl http://0.0.0.0:4000/v1/audio/speech \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -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 ``` #### 語言覆寫 {#language-override} ```bash curl http://0.0.0.0:4000/v1/audio/speech \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -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 特定參數參考 {#azure-specific-parameters-reference} | 參數 | 說明 | 範例值 | 備註 | |-----------|-------------|----------------|-------| | `style` | 說話風格 | `cheerful`、`sad`、`angry`、`excited`、`friendly`、`hopeful`、`shouting`、`terrified`、`unfriendly`、`whispering` | 僅部分語音支援。請參閱 [Azure 語音風格文件](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-synthesis-markup-voice#use-speaking-styles-and-roles) | | `styledegree` | 風格強度 | `0.01` 到 `2` | 數值越高 = 越強烈。預設為 `1` | | `role` | 語音角色 | `Girl`、`Boy`、`YoungAdultFemale`、`YoungAdultMale`、`OlderAdultFemale`、`OlderAdultMale`、`SeniorFemale`、`SeniorMale` | 僅部分語音支援 | | `lang` | 語言代碼 | `es-ES`、`fr-FR`、`de-DE`、`hi-IN` 等 | 適用於多語言語音。覆寫預設語言 | ## 非同步支援 {#async-support} ```python showLineNumbers title="Async Usage" 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()) ``` ## 區域端點 {#regional-endpoints} 請將 `{region}` 替換為您的 Azure 資源區域： - 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` [完整區域清單](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/regions) ## 進階功能 {#advanced-features} ### 自訂 Neural 語音 {#custom-neural-voices} 您可以透過傳入完整語音名稱來使用任何 Azure Neural 語音： ```python showLineNumbers title="Custom Voice" 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"], ) ``` 在 [Azure Speech Gallery](https://speech.microsoft.com/portal/voicegallery) 瀏覽可用語音。 ## 錯誤處理 {#error-handling} ```python showLineNumbers title="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}") ``` ## 參考資料 {#reference} - [Azure Speech Service 文件](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/) - [Text-to-Speech REST API](https://learn.microsoft.com/en-us/azure/ai-services/speech-service/rest-text-to-speech) ## Related pages - [Azure 文件智慧 OCR](https://docs.litellm.ai/docs/providers/azure_document_intelligence.md) - [Azure AI 圖像生成（Black Forest Labs - Flux）](https://docs.litellm.ai/docs/providers/azure_ai_img.md)