Chirp 3：即时自定义语音

import requests, os, json  def create_instant_custom_voice_key(     access_token, project_id, reference_audio_bytes, consent_audio_bytes ):     url = "https://texttospeech.googleapis.com/v1beta1/voices:generateVoiceCloningKey"      request_body = {         "reference_audio": {             # Supported audio_encoding values are LINEAR16, PCM, MP3, and M4A.             "audio_config": {"audio_encoding": "LINEAR16"},             "content": reference_audio_bytes,         },         "voice_talent_consent": {             # Supported audio_encoding values are LINEAR16, PCM, MP3, and M4A.             "audio_config": {"audio_encoding": "LINEAR16"},             "content": consent_audio_bytes,         },         "consent_script": "I am the owner of this voice and I consent to Google using this voice to create a synthetic voice model.",         "language_code": "en-US",     }      try:         headers = {             "Authorization": f"Bearer {access_token}",             "x-goog-user-project": project_id,             "Content-Type": "application/json; charset=utf-8",         }          response = requests.post(url, headers=headers, json=request_body)         response.raise_for_status()          response_json = response.json()         return response_json.get("voiceCloningKey")      except requests.exceptions.RequestException as e:         print(f"Error making API request: {e}")     except json.JSONDecodeError as e:         print(f"Error decoding JSON response: {e}")     except Exception as e:         print(f"An unexpected error occurred: {e}") 

import requests, os, json, base64 from IPython.display import Audio, display  def synthesize_text_with_cloned_voice(access_token, project_id, voice_key, text):     url = "https://texttospeech.googleapis.com/v1beta1/text:synthesize"      request_body = {         "input": {             "text": text         },         "voice": {             "language_code": "en-US",             "voice_clone": {                 "voice_cloning_key": voice_key,             }         },         "audioConfig": {             # Supported audio_encoding values are LINEAR16, PCM, MP3, and M4A.             "audioEncoding": "LINEAR16",         }     }      try:         headers = {             "Authorization": f"Bearer {access_token}",             "x-goog-user-project": project_id,             "Content-Type": "application/json; charset=utf-8"         }          response = requests.post(url, headers=headers, json=request_body)         response.raise_for_status()          response_json = response.json()         audio_content = response_json.get("audioContent")          if audio_content:             display(Audio(base64.b64decode(audio_content), rate=24000))         else:             print("Error: Audio content not found in the response.")             print(response_json)      except requests.exceptions.RequestException as e:         print(f"Error making API request: {e}")     except json.JSONDecodeError as e:         print(f"Error decoding JSON response: {e}")     except Exception as e:         print(f"An unexpected error occurred: {e}") 

from google.cloud import texttospeech from google.cloud.texttospeech_v1beta1.services.text_to_speech import client   def perform_voice_cloning(     voice_cloning_key: str,     transcript: str,     language_code: str,     synthesis_output_path: str,     tts_client: client.TextToSpeechClient, ) -> None:   """Perform voice cloning and write output to a file.    Args:     voice_cloning_key: The voice cloning key.     transcript: The transcript to synthesize.     language_code: The language code.     synthesis_output_path: The synthesis audio output path.     tts_client: The TTS client to use.   """   voice_clone_params = texttospeech.VoiceCloneParams(       voice_cloning_key=voice_cloning_key   )   voice = texttospeech.VoiceSelectionParams(       language_code=language_code, voice_clone=voice_clone_params   )   request = texttospeech.SynthesizeSpeechRequest(       input=texttospeech.SynthesisInput(text=transcript),       voice=voice,       audio_config=texttospeech.AudioConfig(           audio_encoding=texttospeech.AudioEncoding.LINEAR16,           sample_rate_hertz=24000,       ),   )   response = tts_client.synthesize_speech(request)   with open(synthesis_output_path, 'wb') as out:     out.write(response.audio_content)     print(f'Audio content written to file {synthesis_output_path}.')   if __name__ == '__main__':   client = texttospeech.TextToSpeechClient()   with open('voice_cloning_key.txt', 'r') as f:     key = f.read()   perform_voice_cloning(       voice_cloning_key=key,       transcript='Hello world!',       language_code='en-US',       synthesis_output_path='/tmp/output.wav',       tts_client=client,   ) 

import io import wave from google.cloud import texttospeech from google.cloud.texttospeech_v1beta1.services.text_to_speech import client   def perform_voice_cloning_with_simulated_streaming(     voice_cloning_key: str,     simulated_streamed_text: list[str],     language_code: str,     synthesis_output_path: str,     tts_client: client.TextToSpeechClient, ) -> None:   """Perform voice cloning for a given reference audio, voice talent consent, and consent script.    Args:     voice_cloning_key: The voice cloning key.     simulated_streamed_text: The list of transcripts to synthesize, where each       item represents a chunk of streamed text. This is used to simulate       streamed text input and is not meant to be representative of real-world       streaming usage.     language_code: The language code.     synthesis_output_path: The path to write the synthesis audio output to.     tts_client: The TTS client to use.   """   voice_clone_params = texttospeech.VoiceCloneParams(       voice_cloning_key=voice_cloning_key   )   streaming_config = texttospeech.StreamingSynthesizeConfig(       voice=texttospeech.VoiceSelectionParams(           language_code=language_code, voice_clone=voice_clone_params       ),       streaming_audio_config=texttospeech.StreamingAudioConfig(           audio_encoding=texttospeech.AudioEncoding.PCM,           sample_rate_hertz=24000,       ),   )   config_request = texttospeech.StreamingSynthesizeRequest(       streaming_config=streaming_config   )    # Request generator. Consider using Gemini or another LLM with output   # streaming as a generator.   def request_generator():     yield config_request     for text in simulated_streamed_text:       yield texttospeech.StreamingSynthesizeRequest(           input=texttospeech.StreamingSynthesisInput(text=text)       )    streaming_responses = tts_client.streaming_synthesize(request_generator())   audio_buffer = io.BytesIO()   for response in streaming_responses:     print(f'Audio content size in bytes is: {len(response.audio_content)}')     audio_buffer.write(response.audio_content)    # Write collected audio outputs to a WAV file.   with wave.open(synthesis_output_path, 'wb') as wav_file:     wav_file.setnchannels(1)     wav_file.setsampwidth(2)     wav_file.setframerate(24000)     wav_file.writeframes(audio_buffer.getvalue())     print(f'Audio content written to file {synthesis_output_path}.')   if __name__ == '__main__':   client = texttospeech.TextToSpeechClient()   with open('voice_cloning_key.txt', 'r') as f:     key = f.read()   perform_voice_cloning_with_simulated_streaming(       voice_cloning_key=key,       simulated_streamed_text=[           'Hello world!',           'This is the second text chunk.',           'This simulates streaming text for synthesis.',       ],       language_code='en-US',       synthesis_output_path='streaming_output.wav',       tts_client=client,   ) 

voice_clone_params = texttospeech.VoiceCloneParams(     voice_cloning_key=en_us_voice_cloning_key ) request = texttospeech.SynthesizeSpeechRequest(   input=texttospeech.SynthesisInput(text=transcript),   voice=texttospeech.VoiceSelectionParams(       language_code='es-ES', voice_clone=voice_clone_params   ),   audio_config=texttospeech.AudioConfig(       audio_encoding=texttospeech.AudioEncoding.LINEAR16,       sample_rate_hertz=24000,   ), ) 

voice_clone_params = texttospeech.VoiceCloneParams(     voice_cloning_key=en_us_voice_cloning_key ) streaming_config = texttospeech.StreamingSynthesizeConfig(     voice=texttospeech.VoiceSelectionParams(         language_code='es-ES', voice_clone=voice_clone_params     ),     streaming_audio_config=texttospeech.StreamingAudioConfig(         audio_encoding=texttospeech.AudioEncoding.PCM,         sample_rate_hertz=24000,     ), )