From fb1cdf243d1a6852edf1204de5615f7e58fc983c Mon Sep 17 00:00:00 2001 From: ikaros <327209194@qq.com> Date: Tue, 27 Feb 2024 17:33:03 +0800 Subject: [PATCH] =?UTF-8?q?=E8=A1=A5=E5=85=85=E5=8A=A8=E6=80=81=E6=96=87?= =?UTF-8?q?=E6=A1=88=E5=92=8C=E9=97=B2=E6=97=B6=E4=BB=BB=E5=8A=A1=E9=BB=98?= =?UTF-8?q?=E8=AE=A4=E6=95=B0=E6=8D=AE=EF=BC=9B=E6=9B=B4=E6=96=B0=E6=8A=95?= =?UTF-8?q?=E8=B5=84=E4=BA=BA=E4=BF=A1=E6=81=AF?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../AI-Vtuber\344\273\213\347\273\215.txt" | 7 ++++++ ...0\345\215\225\350\256\262\350\247\243.txt" | 7 ++++++ ...0\345\215\225\350\256\262\350\247\243.txt" | 16 ++++++++++++++ ...0\345\215\225\350\256\262\350\247\243.txt" | 15 +++++++++++++ ...0\346\234\257\350\256\262\350\247\243.txt" | 20 ++++++++++++++++++ ...2\344\274\227\345\212\240\347\276\244.txt" | 5 +++++ .../AI-Vtuber\344\273\213\347\273\215.wav" | Bin 0 -> 5949484 bytes ...2\344\274\227\345\212\240\347\276\244.wav" | Bin 0 -> 2254124 bytes .../index.html" | 20 +++++++++++++----- .../invest.png" | Bin 700283 -> 5495815 bytes 10 files changed, 85 insertions(+), 5 deletions(-) create mode 100644 "data/\345\212\250\346\200\201\346\226\207\346\241\2102/AI-Vtuber\344\273\213\347\273\215.txt" create mode 100644 "data/\345\212\250\346\200\201\346\226\207\346\241\2102/LLM\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" create mode 100644 "data/\345\212\250\346\200\201\346\226\207\346\241\2102/STT\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" create mode 100644 "data/\345\212\250\346\200\201\346\226\207\346\241\2102/TTS\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" create mode 100644 "data/\345\212\250\346\200\201\346\226\207\346\241\2102/VITS\346\212\200\346\234\257\350\256\262\350\247\243.txt" create mode 100644 "data/\345\212\250\346\200\201\346\226\207\346\241\2102/\351\202\200\350\257\267\350\247\202\344\274\227\345\212\240\347\276\244.txt" create mode 100644 "data/\351\227\262\346\227\266\344\273\273\345\212\241/\351\237\263\351\242\221/ai_vtb/AI-Vtuber\344\273\213\347\273\215.wav" create mode 100644 "data/\351\227\262\346\227\266\344\273\273\345\212\241/\351\237\263\351\242\221/ai_vtb/\351\202\200\350\257\267\350\247\202\344\274\227\345\212\240\347\276\244.wav" diff --git "a/data/\345\212\250\346\200\201\346\226\207\346\241\2102/AI-Vtuber\344\273\213\347\273\215.txt" "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/AI-Vtuber\344\273\213\347\273\215.txt" new file mode 100644 index 00000000..15aa782f --- /dev/null +++ "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/AI-Vtuber\344\273\213\347\273\215.txt" @@ -0,0 +1,7 @@ +AI Vtuber 是一款结合了最先进技术的虚拟AI主播。它的核心是一系列高效的人工智能模型。包括 ChatterBot、GPT、Claude、langchain、chatglm、text-generation-webui、讯飞星火、智谱AI、谷歌Bard、文心一言、通义星尘、千帆大模型、Gemini、Kimi Chat、QAnything、koboldcpp。这些模型既可以在本地运行,也可以通过云端服务提供支持。 + +AI Vtuber 的外观由 Live2D、Vtube Studio、xuniren 和 UE5 结合 Audio2Face 技术打造。为用户提供了一个生动、互动的虚拟形象。这使得 AI Vtuber 能够在各大直播平台。如 Bilibili、抖音、快手、微信视频号、斗鱼、YouTube、Twitch 和 TikTok,进行实时互动直播。当然,它也可以在本地环境中与您进行个性化对话。 + +为了使交流更加自然,AI Vtuber 使用了先进的自然语言处理技术,结合文本转语音系统。如Edge-TTS、VITS-Fast、elevenlabs、bark-gui、VALL-E-X、睿声AI、genshinvoice.top、tts.ai-lab.top、OpenVoice、GPT_SoVITS、clone-voice、Azure TTS。这不仅让它能够生成流畅的回答,还可以通过 so-vits-svc 和 DDSP-SVC 实现声音的变化,以适应不同的场景和角色。 + +此外,AI Vtuber 还能够通过特定指令与 Stable Diffusion 协作,展示画作。用户还可以自定义文案,让 AI Vtuber 循环播放,以满足不同场合的需求。 \ No newline at end of file diff --git "a/data/\345\212\250\346\200\201\346\226\207\346\241\2102/LLM\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/LLM\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" new file mode 100644 index 00000000..e2530d80 --- /dev/null +++ "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/LLM\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" @@ -0,0 +1,7 @@ +LLM技术通常指大型语言模型(Large Language Model),是一种基于机器学习和自然语言处理的技术。这种技术通过训练大规模的神经网络模型,以便理解和生成自然语言文本。 + +大型语言模型通常具有数十亿甚至数万亿个参数,可以通过大规模的文本语料库进行预训练。在预训练阶段,模型会学习语言的结构、语法规则和语义信息,从而能够在后续任务中生成自然流畅的文本或者理解输入的文本。 + +LLM技术在自然语言处理领域有着广泛的应用,包括机器翻译、文本摘要、问答系统、语言理解和生成等任务。近年来,随着深度学习技术的不断发展,大型语言模型在这些任务中取得了令人瞩目的成果,如GPT(Generative Pre-trained Transformer)系列模型、BERT(Bidirectional Encoder Representations from Transformers)模型等。 + +LLM技术的发展为自然语言处理领域带来了许多新的可能性,使得计算机能够更好地理解和生成自然语言,为人机交互和信息处理提供了更多的可能性。 \ No newline at end of file diff --git "a/data/\345\212\250\346\200\201\346\226\207\346\241\2102/STT\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/STT\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" new file mode 100644 index 00000000..295804f1 --- /dev/null +++ "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/STT\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" @@ -0,0 +1,16 @@ + +STT技术指的是语音到文本技术(Speech-to-Text),也被称为语音识别技术,是一种将人类语音转换为书面文本的技术。这种技术在人工智能和自然语言处理领域得到广泛应用,可以帮助计算机理解和处理语音输入。 + +STT技术的工作原理通常包括以下几个步骤: + +语音采集:首先,系统需要收集用户的语音输入,可以通过麦克风或其他音频设备进行采集。 + +语音预处理:接下来,系统对采集到的语音信号进行预处理,包括去噪、降噪、音频增益调整等,以提高后续处理的准确性。 + +特征提取:系统将预处理后的语音信号转换为数字特征向量,通常使用的方法包括MFCC(Mel-frequency cepstral coefficients)等。 + +语音识别模型:系统使用训练好的语音识别模型对特征向量进行识别,将其转换为文本。 + +后处理:最后,系统对识别的文本进行后处理,包括语法纠正、语言模型调整等,以提高识别准确性。 + +STT技术在语音识别、语音助手、语音转换文本、实时字幕生成等领域有着广泛的应用。随着深度学习和神经网络技术的发展,STT技术的准确性和性能得到了很大的提升,使得语音输入成为了人机交互的重要方式之一。 \ No newline at end of file diff --git "a/data/\345\212\250\346\200\201\346\226\207\346\241\2102/TTS\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/TTS\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" new file mode 100644 index 00000000..55f3585e --- /dev/null +++ "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/TTS\346\212\200\346\234\257\347\256\200\345\215\225\350\256\262\350\247\243.txt" @@ -0,0 +1,15 @@ +TTS技术是指文本到语音技术(Text-to-Speech),它是一种人工智能技术,能够将书面文本转换为自然语音。这种技术背后的原理涉及到深度学习和语音合成领域的知识。 + +简单来说,TTS技术可以分为以下几个步骤: + +文本分析:首先,系统会对输入的文本进行分析,包括识别单词、句子结构和语法规则等。 + +语言处理:接着,系统会根据分析的结果,确定合适的语音合成规则和模型,以及语音库中相应的语音单元。 + +语音合成:在这一步中,系统会根据文本的内容和语言规则,使用预先训练好的模型,将文本转换为语音。 + +音色选择:TTS系统通常会提供多种不同的音色选择,用户可以根据自己的喜好或需要选择合适的音色。 + +语音输出:最后,系统会输出经过处理的语音,让用户可以听到转换后的语音内容。 + +TTS技术在很多领域都有应用,比如辅助阅读、语音助手、教育培训等。通过TTS技术,计算机可以更直观地与用户交流,提供更便捷的服务和体验。 \ No newline at end of file diff --git "a/data/\345\212\250\346\200\201\346\226\207\346\241\2102/VITS\346\212\200\346\234\257\350\256\262\350\247\243.txt" "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/VITS\346\212\200\346\234\257\350\256\262\350\247\243.txt" new file mode 100644 index 00000000..af6c0566 --- /dev/null +++ "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/VITS\346\212\200\346\234\257\350\256\262\350\247\243.txt" @@ -0,0 +1,20 @@ +VITS(Variational Inference with adversarial learning for end-to-end Text-to-Speech)是一种端到端的文本到语音(Text-to-Speech,TTS)合成技术。这种技术结合了变分自编码器(Variational Autoencoder,VAE)和生成对抗网络(Generative Adversarial Networks,GANs)的原理,旨在生成高质量、自然 sounding 的语音输出。 + +VITS的主要特点和优势包括: + +1. 端到端系统 +与传统的TTS系统相比,其中可能需要多个步骤来从文本转换到语音(例如,文本分析、声学模型、声码器等),VITS提供了一个端到端的解决方案,可以直接从原始文本生成语音波形,简化了整个流程。 + +2. 变分推断 +VITS使用变分自编码器(VAE)来学习语音数据的潜在表示,这有助于生成更多样化且自然 sounding 的语音。VAE通过编码输入数据到一个潜在空间,并从这个空间解码以重构输入数据,使模型能够捕捉到数据的关键特征。 + +3. 对抗性学习 +通过集成GANs,VITS在生成语音时引入了对抗性学习机制。在这个框架中,生成器(Generator)负责生成尽可能逼真的语音,而判别器(Discriminator)的任务是区分生成的语音和真实的语音。这种对抗性的过程使得生成的语音质量显著提高,更接近于真实人类的语音。 + +4. 高质量语音合成 +VITS能够生成高质量、自然 sounding 的语音,且在合成速度和合成质量方面都表现优异。这使得VITS特别适用于需要高质量语音输出的应用场景,如虚拟助手、有声读物、动画角色配音等。 + +5. 灵活性和通用性 +VITS模型能够适应不同的语言和声音,使其成为一个通用的TTS解决方案。此外,它可以根据需要调整,以生成具有不同情感或风格的语音,增加了合成语音的多样性和应用范围。 + +VITS技术通过这些创新,显著提升了文本到语音转换的质量和效率,使其在TTS领域成为一项前沿技术。 \ No newline at end of file diff --git "a/data/\345\212\250\346\200\201\346\226\207\346\241\2102/\351\202\200\350\257\267\350\247\202\344\274\227\345\212\240\347\276\244.txt" "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/\351\202\200\350\257\267\350\247\202\344\274\227\345\212\240\347\276\244.txt" new file mode 100644 index 00000000..d29c4cd0 --- /dev/null +++ "b/data/\345\212\250\346\200\201\346\226\207\346\241\2102/\351\202\200\350\257\267\350\247\202\344\274\227\345\212\240\347\276\244.txt" @@ -0,0 +1,5 @@ +欢迎大家来到我的直播间,当前运行的功能是“定时任务”。 +本项目名为:AI Vtuber,完全开源免费,大家可以进入我的主页,观看合集教程进行安装部署使用。 +具体功能有对应的视频讲解,请大家耐心观看学习。 +如果遇到部署及使用问题,可以到官方仓库提交issue,或者加入我的QQ群:587663288。 +简单问题可以快速交流,复杂问题或者定制需求,可以联系我的主人进行定制化开发。 \ No newline at end of file diff --git "a/data/\351\227\262\346\227\266\344\273\273\345\212\241/\351\237\263\351\242\221/ai_vtb/AI-Vtuber\344\273\213\347\273\215.wav" "b/data/\351\227\262\346\227\266\344\273\273\345\212\241/\351\237\263\351\242\221/ai_vtb/AI-Vtuber\344\273\213\347\273\215.wav" new file mode 100644 index 0000000000000000000000000000000000000000..0d1fb85a106eb71da8c2f8bfb983be423b7ab85d GIT binary patch literal 5949484 zcmYhj3w%@M{XhPkoLt+aO|PUEN_wFLC=jqMMSNRX>@gF z$TU-Qop#!3)s8WZ+F`+h6)Qw6P@zERHNB^8+NQalB$JgNn5&{o` z0BZs@dVU662P*IhXK+{i|ILFL!1sbIKuN&#fr=Q(kOYqhTGTu>!Y_;`k`m5EcoaP^ zB|_5qb65{}g%?>Hcm^tBJVH!v%yWY9cm-Yu4$1soLIHS(mjsU|XQKIeKm{xSx&Ub; z_#iJ~UJCfTU+Z6_yL`>SYlWSu1YaCz=s&Gz|SKCbO3Y7 z`r>(B;F|>NA1no0UErCFWbiyGN<#7fTR(_V#LwFXBmfG)8Hc$de87rQtP7AA?gD3^ 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