安装python包
#安装 Kokoro 主包pipinstallkokoro
下载模型
#安装modelscope包。通过modelscope下载pipinstallmodelscope#下载模型, local_dir指定下载位置modelscope download--modelAI-ModelScope/Kokoro-82M-v1.1-zh README.md--local_dir./dir
简单使用
fromkokoroimportKPipeline,KModel# from IPython.display import display, Audioimportsoundfileassf# 参数中config与model修改为本地模型路径model=KModel(config='../model/config.json',model='../model/kokoro-v1_1-zh.pth')pipeline=KPipeline(lang_code='zh',model=model)text='使用kokoro-tts的测试'# 下方voice修改为本地对应模型路径generator=pipeline(text,voice='../model/voices/zm_yunxi.pt',# <= change voice herespeed=0.85,split_pattern=r'[,,.。!!??;;\n]+',# noise_scale=0.667, # 调整噪声比例# noise_scale_w=0.8, # 调整音素持续时间的变化# length_scale=1.0 # 调整语音长度)all_audio_segments=[]# for i, (gs, ps, audio) in enumerate(generator):# print(i) # i => index# print(gs) # gs => graphemes/text# print(ps) # ps => phonemes# display(Audio(data=audio, rate=24000, autoplay=i==0))# sf.write(f'{i}.wav', audio, 24000)fori,(gs,ps,audio)inenumerate(generator):print(f"处理第{i+1}段:")print(f"文本:{gs}")# 打印当前处理的文本print(f"音素:{ps}")# 打印音素all_audio_segments.append(audio)# 可以选择是否保存单独的片段sf.write(f'./output/segment_{i}.wav',audio,24000)# 合并所有音频片段importnumpyasnp combined_audio=np.concatenate(all_audio_segments)sf.write('./output/complete_audio.wav',combined_audio,24000)print("所有片段已合并并保存为 complete_audio.wav")