Alibaba Cloud Model Studio：即時語音合成-CosyVoice

import os
import time
import dashscope
from dashscope.audio.tts_v2 import VoiceEnrollmentService, SpeechSynthesizer

# 1. 環境準備
# 推薦通過環境變數配置API Key
# 新加坡和北京地區的API Key不同。擷取API Key：https://www.alibabacloud.com/help/zh/model-studio/get-api-key
# 若沒有配置環境變數，請用百鍊API Key將下行替換為：dashscope.api_key = "sk-xxx"
dashscope.api_key = os.getenv("DASHSCOPE_API_KEY")
if not dashscope.api_key:
    raise ValueError("DASHSCOPE_API_KEY environment variable not set.")

# 以下為新加坡地區WebSocket url，若使用北京地區的模型，需將url替換為：wss://dashscope.aliyuncs.com/api-ws/v1/inference
dashscope.base_websocket_api_url='wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference'
# 以下為新加坡地區HTTP url，若使用北京地區的模型，需將url替換為：https://dashscope.aliyuncs.com/api/v1
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.com/api/v1'


# 2. 定義複刻參數
TARGET_MODEL = "cosyvoice-v3.5-plus" 
# 為音色起一個有意義的首碼
VOICE_PREFIX = "myvoice" # 僅允許數字和小寫字母，小於十個字元
# 公網可訪問音頻URL
AUDIO_URL = "https://dashscope.oss-cn-beijing.aliyuncs.com/samples/audio/cosyvoice/cosyvoice-zeroshot-sample.wav" # 樣本URL，請替換為自己的

# 3. 建立音色 (非同步任務)
print("--- Step 1: Creating voice enrollment ---")
service = VoiceEnrollmentService()
try:
    voice_id = service.create_voice(
        target_model=TARGET_MODEL,
        prefix=VOICE_PREFIX,
        url=AUDIO_URL
    )
    print(f"Voice enrollment submitted successfully. Request ID: {service.get_last_request_id()}")
    print(f"Generated Voice ID: {voice_id}")
except Exception as e:
    print(f"Error during voice creation: {e}")
    raise e
# 4. 輪詢查詢音色狀態
print("\n--- Step 2: Polling for voice status ---")
max_attempts = 30
poll_interval = 10 # 秒
for attempt in range(max_attempts):
    try:
        voice_info = service.query_voice(voice_id=voice_id)
        status = voice_info.get("status")
        print(f"Attempt {attempt + 1}/{max_attempts}: Voice status is '{status}'")
        
        if status == "OK":
            print("Voice is ready for synthesis.")
            break
        elif status == "UNDEPLOYED":
            print(f"Voice processing failed with status: {status}. Please check audio quality or contact support.")
            raise RuntimeError(f"Voice processing failed with status: {status}")
        # 對於 "DEPLOYING" 等中間狀態，繼續等待
        time.sleep(poll_interval)
    except Exception as e:
        print(f"Error during status polling: {e}")
        time.sleep(poll_interval)
else:
    print("Polling timed out. The voice is not ready after several attempts.")
    raise RuntimeError("Polling timed out. The voice is not ready after several attempts.")

# 5. 使用複刻音色進行語音合成
print("\n--- Step 3: Synthesizing speech with the new voice ---")
try:
    synthesizer = SpeechSynthesizer(model=TARGET_MODEL, voice=voice_id)
    text_to_synthesize = "恭喜，已成功複刻併合成了屬於自己的聲音！"
    
    # call()方法返回二進位音頻資料
    audio_data = synthesizer.call(text_to_synthesize)
    print(f"Speech synthesis successful. Request ID: {synthesizer.get_last_request_id()}")

    # 6. 儲存音頻檔案
    output_file = "my_custom_voice_output.mp3"
    with open(output_file, "wb") as f:
        f.write(audio_data)
    print(f"Audio saved to {output_file}")

except Exception as e:
    print(f"Error during speech synthesis: {e}")

1. 產生專屬音色並試聽效果，若對效果滿意，進行下一步；否則重建。

   Python

   import requests
   import base64
   import os
   
   def create_voice_and_play():
       # 新加坡和北京地區的API Key不同。擷取API Key：https://www.alibabacloud.com/help/zh/model-studio/get-api-key
       # 若沒有配置環境變數，請用百鍊API Key將下行替換為：api_key = "sk-xxx"
       api_key = os.getenv("DASHSCOPE_API_KEY")
       
       if not api_key:
           print("錯誤: 未找到DASHSCOPE_API_KEY環境變數，請先設定API Key")
           return None, None, None
       
       # 準備請求資料
       headers = {
           "Authorization": f"Bearer {api_key}",
           "Content-Type": "application/json"
       }
       
       data = {
           "model": "voice-enrollment",
           "input": {
               "action": "create_voice",
               "target_model": "cosyvoice-v3.5-plus",
               "voice_prompt": "A composed middle-aged male announcer with a deep, rich and magnetic voice, a steady speaking speed and clear articulation, is suitable for news broadcasting or documentary commentary.",
               "preview_text": "Dear listeners, hello everyone. Welcome to the evening news.",
               "prefix": "announcer"
           },
           "parameters": {
               "sample_rate": 24000,
               "response_format": "wav"
           }
       }
       
       # 以下為新加坡地區url，若使用北京地區的模型，需將url替換為：https://dashscope.aliyuncs.com/api/v1/services/audio/tts/customization
       url = "https://dashscope-intl.aliyuncs.com/api/v1/services/audio/tts/customization"
       
       try:
           # 發送請求
           response = requests.post(
               url,
               headers=headers,
               json=data,
               timeout=60  # 添加逾時設定
           )
           
           if response.status_code == 200:
               result = response.json()
               
               # 擷取音色ID
               voice_id = result["output"]["voice_id"]
               print(f"音色ID: {voice_id}")
               
               # 擷取預覽音頻資料
               base64_audio = result["output"]["preview_audio"]["data"]
               
               # 解碼Base64音頻資料
               audio_bytes = base64.b64decode(base64_audio)
               
               # 儲存音頻檔案到本地
               filename = f"{voice_id}_preview.wav"
               
               # 將音頻資料寫入本地檔案
               with open(filename, 'wb') as f:
                   f.write(audio_bytes)
               
               print(f"音頻已儲存到本地檔案: {filename}")
               print(f"檔案路徑: {os.path.abspath(filename)}")
               
               return voice_id, audio_bytes, filename
           else:
               print(f"請求失敗，狀態代碼: {response.status_code}")
               print(f"響應內容: {response.text}")
               return None, None, None
               
       except requests.exceptions.RequestException as e:
           print(f"網路請求發生錯誤: {e}")
           return None, None, None
       except KeyError as e:
           print(f"響應資料格式錯誤，缺少必要的欄位: {e}")
           print(f"響應內容: {response.text if 'response' in locals() else 'No response'}")
           return None, None, None
       except Exception as e:
           print(f"發生未知錯誤: {e}")
           return None, None, None
   
   if __name__ == "__main__":
       print("開始建立語音...")
       voice_id, audio_data, saved_filename = create_voice_and_play()
       
       if voice_id:
           print(f"\n成功建立音色 '{voice_id}'")
           print(f"音頻檔案已儲存: '{saved_filename}'")
           print(f"檔案大小: {os.path.getsize(saved_filename)} 位元組")
       else:
           print("\n音色建立失敗")

   Java

   需要匯入Gson依賴，若是使用Maven或者Gradle，添加依賴方式如下：

   Maven

   在pom.xml中添加如下內容：

   <!-- https://mvnrepository.com/artifact/com.google.code.gson/gson -->
   <dependency>
       <groupId>com.google.code.gson</groupId>
       <artifactId>gson</artifactId>
       <version>2.13.1</version>
   </dependency>

   Gradle

   在build.gradle中添加如下內容：

   // https://mvnrepository.com/artifact/com.google.code.gson/gson
   implementation("com.google.code.gson:gson:2.13.1")

   import com.google.gson.JsonObject;
   import com.google.gson.JsonParser;
   import java.io.*;
   import java.net.HttpURLConnection;
   import java.net.URL;
   import java.util.Base64;
   
   public class Main {
       public static void main(String[] args) {
           Main example = new Main();
           example.createVoice();
       }
   
       public void createVoice() {
           // 新加坡和北京地區的API Key不同。擷取API Key：https://www.alibabacloud.com/help/zh/model-studio/get-api-key
           // 若沒有配置環境變數，請用百鍊API Key將下行替換為：String apiKey = "sk-xxx"
           String apiKey = System.getenv("DASHSCOPE_API_KEY");
   
           // 建立JSON請求體字串
           String jsonBody = "{\n" +
                   "    \"model\": \"voice-enrollment\",\n" +
                   "    \"input\": {\n" +
                   "        \"action\": \"create_voice\",\n" +
                   "        \"target_model\": \"cosyvoice-v3.5-plus\",\n" +
                   "        \"voice_prompt\": \"A composed middle-aged male announcer with a deep, rich and magnetic voice, a steady speaking speed and clear articulation, is suitable for news broadcasting or documentary commentary.\",\n" +
                   "        \"preview_text\": \"Dear listeners, hello everyone. Welcome to the evening news.\",\n" +
                   "        \"prefix\": \"announcer\"\n" +
                   "    },\n" +
                   "    \"parameters\": {\n" +
                   "        \"sample_rate\": 24000,\n" +
                   "        \"response_format\": \"wav\"\n" +
                   "    }\n" +
                   "}";
   
           HttpURLConnection connection = null;
           try {
               // 以下為新加坡地區url，若使用北京地區的模型，需將url替換為：https://dashscope.aliyuncs.com/api/v1/services/audio/tts/customization
               URL url = new URL("https://dashscope-intl.aliyuncs.com/api/v1/services/audio/tts/customization");
               connection = (HttpURLConnection) url.openConnection();
   
               // 佈建要求方法和頭部
               connection.setRequestMethod("POST");
               connection.setRequestProperty("Authorization", "Bearer " + apiKey);
               connection.setRequestProperty("Content-Type", "application/json");
               connection.setDoOutput(true);
               connection.setDoInput(true);
   
               // 發送請求體
               try (OutputStream os = connection.getOutputStream()) {
                   byte[] input = jsonBody.getBytes("UTF-8");
                   os.write(input, 0, input.length);
                   os.flush();
               }
   
               // 擷取響應
               int responseCode = connection.getResponseCode();
               if (responseCode == HttpURLConnection.HTTP_OK) {
                   // 讀取響應內容
                   StringBuilder response = new StringBuilder();
                   try (BufferedReader br = new BufferedReader(
                           new InputStreamReader(connection.getInputStream(), "UTF-8"))) {
                       String responseLine;
                       while ((responseLine = br.readLine()) != null) {
                           response.append(responseLine.trim());
                       }
                   }
   
                   // 解析JSON響應
                   JsonObject jsonResponse = JsonParser.parseString(response.toString()).getAsJsonObject();
                   JsonObject outputObj = jsonResponse.getAsJsonObject("output");
                   JsonObject previewAudioObj = outputObj.getAsJsonObject("preview_audio");
   
                   // 擷取音色名稱
                   String voiceId = outputObj.get("voice_id").getAsString();
                   System.out.println("音色ID: " + voiceId);
   
                   // 擷取Base64編碼的音頻資料
                   String base64Audio = previewAudioObj.get("data").getAsString();
   
                   // 解碼Base64音頻資料
                   byte[] audioBytes = Base64.getDecoder().decode(base64Audio);
   
                   // 儲存音頻到本地檔案
                   String filename = voiceId + "_preview.wav";
                   saveAudioToFile(audioBytes, filename);
   
                   System.out.println("音頻已儲存到本地檔案: " + filename);
   
               } else {
                   // 讀取錯誤響應
                   StringBuilder errorResponse = new StringBuilder();
                   try (BufferedReader br = new BufferedReader(
                           new InputStreamReader(connection.getErrorStream(), "UTF-8"))) {
                       String responseLine;
                       while ((responseLine = br.readLine()) != null) {
                           errorResponse.append(responseLine.trim());
                       }
                   }
   
                   System.out.println("請求失敗，狀態代碼: " + responseCode);
                   System.out.println("錯誤響應: " + errorResponse.toString());
               }
   
           } catch (Exception e) {
               System.err.println("請求發生錯誤: " + e.getMessage());
               e.printStackTrace();
           } finally {
               if (connection != null) {
                   connection.disconnect();
               }
           }
       }
   
       private void saveAudioToFile(byte[] audioBytes, String filename) {
           try {
               File file = new File(filename);
               try (FileOutputStream fos = new FileOutputStream(file)) {
                   fos.write(audioBytes);
               }
               System.out.println("音頻已儲存到: " + file.getAbsolutePath());
           } catch (IOException e) {
               System.err.println("儲存音頻檔案時發生錯誤: " + e.getMessage());
               e.printStackTrace();
           }
       }
   }

2. 使用上一步產生的專屬音色進行語音合成。

   這裡參考了非流式調用範例程式碼，將voice參數替換為聲音設計產生的專屬音色進行語音合成。

   關鍵原則：聲音設計時使用的模型 (target_model) 必須與後續進行語音合成時使用的模型 (model) 保持一致，否則會導致合成失敗。

   Python

   # coding=utf-8
   
   import dashscope
   from dashscope.audio.tts_v2 import *
   import os
   
   # 新加坡地區和北京地區的API Key不同。擷取API Key：https://www.alibabacloud.com/help/zh/model-studio/get-api-key
   # 若沒有配置環境變數，請用百鍊API Key將下行替換為：dashscope.api_key = "sk-xxx"
   dashscope.api_key = os.environ.get('DASHSCOPE_API_KEY')
   
   # 以下為新加坡地區url，若使用北京地區的模型，需將url替換為：wss://dashscope.aliyuncs.com/api-ws/v1/inference
   dashscope.base_websocket_api_url='wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference'
   
   # 聲音設計、語音合成要使用相同的模型
   model = "cosyvoice-v3.5-plus"
   # 將voice參數替換為聲音設計產生的專屬音色
   voice = "your_voice"
   
   # 執行個體化SpeechSynthesizer，並在構造方法中傳入模型（model）、音色（voice）等請求參數
   synthesizer = SpeechSynthesizer(model=model, voice=voice)
   # 發送待合成文本，擷取二進位音頻
   audio = synthesizer.call("今天天氣怎麼樣？")
   # 首次發送文本時需建立 WebSocket 串連，因此首包延遲會包含串連建立的耗時
   print('[Metric] requestId為：{}，首包延遲為：{}毫秒'.format(
       synthesizer.get_last_request_id(),
       synthesizer.get_first_package_delay()))
   
   # 將音頻儲存至本地
   with open('output.mp3', 'wb') as f:
       f.write(audio)

   Java

   import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesisParam;
   import com.alibaba.dashscope.audio.ttsv2.SpeechSynthesizer;
   import com.alibaba.dashscope.utils.Constants;
   
   import java.io.File;
   import java.io.FileOutputStream;
   import java.io.IOException;
   import java.nio.ByteBuffer;
   
   public class Main {
       // 聲音設計、語音合成要使用相同的模型
       private static String model = "cosyvoice-v3.5-plus";
       // 將voice參數替換為聲音設計產生的專屬音色
       private static String voice = "your_voice_id";
   
       public static void streamAudioDataToSpeaker() {
           // 請求參數
           SpeechSynthesisParam param =
                   SpeechSynthesisParam.builder()
                           // 新加坡地區和北京地區的API Key不同。擷取API Key：https://www.alibabacloud.com/help/zh/model-studio/get-api-key
                           // 若沒有配置環境變數，請用百鍊API Key將下行替換為：.apiKey("sk-xxx")
                           .apiKey(System.getenv("DASHSCOPE_API_KEY"))
                           .model(model) // 模型
                           .voice(voice) // 音色
                           .build();
   
           // 同步模式：禁用回調（第二個參數為null）
           SpeechSynthesizer synthesizer = new SpeechSynthesizer(param, null);
           ByteBuffer audio = null;
           try {
               // 阻塞直至音頻返回
               audio = synthesizer.call("今天天氣怎麼樣？");
           } catch (Exception e) {
               throw new RuntimeException(e);
           } finally {
               // 任務結束關閉websocket串連
               synthesizer.getDuplexApi().close(1000, "bye");
           }
           if (audio != null) {
               // 將音頻資料儲存到本地檔案“output.mp3”中
               File file = new File("output.mp3");
               // 首次發送文本時需建立 WebSocket 串連，因此首包延遲會包含串連建立的耗時
               System.out.println(
                       "[Metric] requestId為："
                               + synthesizer.getLastRequestId()
                               + "首包延遲（毫秒）為："
                               + synthesizer.getFirstPackageDelay());
               try (FileOutputStream fos = new FileOutputStream(file)) {
                   fos.write(audio.array());
               } catch (IOException e) {
                   throw new RuntimeException(e);
               }
           }
       }
   
       public static void main(String[] args) {
           // 以下為新加坡地區url，若使用北京地區的模型，需將url替換為：wss://dashscope.aliyuncs.com/api-ws/v1/inference
           Constants.baseWebsocketApiUrl = "wss://dashscope-intl.aliyuncs.com/api-ws/v1/inference";
           streamAudioDataToSpeaker();
           System.exit(0);
       }
   }