Learn how deep learning transformed text-to-speech forever. In this video, we explore the neural revolution that began in 2016 with WaveNet and Tacotron, and how these breakthroughs reshaped speech synthesis into what we know today. Discover how end-to-end learning, learned representations, and neural vocoders made synthetic voices sound natural, expressive, and human-like — paving the way for modern systems like FastSpeech, VITS, and VALL-E. This is Video 6 in The Monster Text-to-Speech and Voice Cloning Course, a lecture series designed to give you a deep understanding of state-of-the-art concepts in speech synthesis. 🎯 KEY TOPICS: - The 2016 breakthrough: WaveNet and Tacotron -How end-to-end learning changed speech synthesis - Why neural networks replaced manual feature design - The 2-stage TTS pipeline: acoustic model + vocoder - How mel spectrograms bridge text and audio - Neural vocoders: WaveNet, WaveGlow, HiFi-GAN - Sequence-to-sequence models with attention - Parallel TTS architectures: FastSpeech, GlowTTS - How neural TTS enabled voice cloning and expressiveness - The rise of codec-based generation (VALL-E, AudioLM, SPEAR-TTS) CONSULTING: 🚀 AI Music + Audio Consulting: https://valeriovelardoadvisor.com/ 📩 Get my AI Music content in your inbox for free: https://valeriovelardo.substack.com/ COURSE MATERIALS + DISCUSSION: - GitHub Repository: https://github.com/musikalkemist/tts-voicecloning-course - Join The Sound of AI Slack Community: https://valeriovelardo.com/the-sound-of-ai-community/ (#tts-course channel) Content: 0:00 Intro 0:59 The deep learning breakthrough 6:16 Core neural innovations 10:25 2-stage neural pipeline 16:34 WaveNet 19:40 Tacotron 23:55 What makes neural TTS work 26:47 Parallel neural generation 28:36 Unlocking voice cloning 29:40 Modern TTS architectures 30:40 End-to-end 31:51 Codec-based voice cloning 35:06 Open challenges 38:53 Takeaways

Learn about traditional text-to-speech techniques before the rise of neural networks in 2016. Explore formant synthesis, concatenative synthesis, and statistical parametric (HMM-based) synthesis—the methods that paved the way for modern neural TTS. This is video 5 in The Monster Text-to-Speech and Voice Cloning Course, a lecture series designed to give you a deep understanding of state-of-the-art concepts in speech synthesis. 🎯 KEY TOPICS: - The evolution of speech synthesis before deep learning - How formant synthesis modeled the vocal tract - How concatenative synthesis stitched recorded speech units - The rise of HMM-based (parametric) synthesis - Why pre-neural voices sounded robotic or over-smoothed - How these classic methods paved the way for neural TTS CONSULTING: 🚀 AI Music + Audio Consulting: https://valeriovelardoadvisor.com/ 📩 Get my AI Music content in your inbox for free: https://valeriovelardo.substack.com/ COURSE MATERIALS + DISCUSSION: - GitHub Repository: https://github.com/musikalkemist/tts-voicecloning-course - Join The Sound of AI Slack Community: https://valeriovelardo.com/the-sound-of-ai-community/ (#tts-course channel) Content: 0:00 Intro 4:05 Formant synthesis 7:41 Formant: Pros and cons 12:18 Concatenative synthesis 13:41 Diphone concatenation 15:10 Unit selection 25:20 Concat: Pros and cons 27:55 Statistical parametric synthesis (HMM) 38:57 HMM-based TTS: Pros and cons 42:32 Comparing traditional TTS

In this video, I explain the intuition behind how Text-to-Speech and Voice Cloning models work—and how they differ. This is the fourth video in The Monster Text-to-Speech and Voice Cloning Course, a lecture series designed to give you a deep understanding of state-of-the-art concepts in speech synthesis. 🎯 KEY TOPICS: The intuition behind how AI generates speech The difference between TTS and voice cloning Use cases for TTS vs. voice cloning How these technologies work under the hood Zero-shot and few-shot voice cloning, plus fine-tuning The tradeoffs between data, speed, and quality What speaker embeddings are and why they matter How AI captures voice identity: timbre, accent, rhythm, prosody The key ethical aspects to consider CONSULTING: 🚀 AI Music + Audio Consulting: https://valeriovelardoadvisor.com/ 📩 Get my AI Music content in your inbox for free: https://valeriovelardo.substack.com/ COURSE MATERIALS + DISCUSSION: - GitHub Repository: https://github.com/musikalkemist/tts-voicecloning-course - Join The Sound of AI Slack Community: https://valeriovelardo.com/the-sound-of-ai-community/ (#tts-course channel) Content: 0:00 Intro 0:48 What's TTS? 5:01 Whats voice cloning? 8:56 TTS vs voice cloning 12:17 Voice adaptation spectrum 14:02 Zero-shot 15:14 Few-shot 16:40 Fine-tuning 17:54 Training from scratch 19:17 Speaker embeddings 22:18 How do zero- and few-shot work? 24:18 How does fine-tuning work? 27:47 Quality vs data tradeoff 29:18 Voice cloning products 32:08 Ethical considerations 35:10 Responsible use 37:08 Takeaways

Before AI can speak, it needs to read. This lecture explains how TTS systems process raw text into phonemes - handling everything from numbers and abbreviations to the tricky problem of words that look the same but sound different. This is the third video in The Monster Text-to-Speech and Voice Cloning Course, a lecture series designed to give you a deep understanding of state-of-the-art concepts in speech synthesis. 🎯 KEY TOPICS: - Text normalization: standardizing raw text - Grapheme-to-Phoneme (G2P) conversion - Rule-based approaches (dictionaries + fallback rules) - Learned approaches (seq2seq models) - The homograph problem and ambiguity resolution - Tools: CMUDict, Phonemizer, DeepPhonemizer, g2p_en - Modern end-to-end TTS that learns text processing implicitly CONSULTING: 🚀 AI Music + Audio Consulting: https://valeriovelardoadvisor.com/ 📩 Get my AI Music content in your inbox for free: https://valeriovelardo.substack.com/ COURSE MATERIALS + DISCUSSION: - GitHub Repository: https://github.com/musikalkemist/tts-voicecloning-course - Join The Sound of AI Slack Community: https://valeriovelardo.com/the-sound-of-ai-community/ (#tts-course channel) Content 0:00 Intro 0:12 TTS pipeline 2:20 Text processing 5:00 Normalization 7:31 Normalization tools 9:55 Grapheme-to-phoneme 14:36 Rule-based G2P 19:20 Learned G2P 24:07 Ambiguity problem 33:20 Modern end-to-end TTS 35:38 G2P tools 38:17 Takeaways

Before building AI speech systems, we need to understand how humans actually produce speech. This lecture breaks down the biology and physics of human voice production - from thoughts to sound waves - and explains why creating realistic text-to-speech is so challenging. This is the second video in The Monster Text-to-Speech and Voice Cloning Course, a lecture series designed to give you a deep understanding of state-of-the-art concepts in speech synthesis. 🎯 KEY TOPICS: - The speech pipeline: Thought → Language → Phonemes → Articulation → Sound - Phonemes and the International Phonetic Alphabet (IPA) - Source-filter model of speech production - Vocal folds, formants, and resonance - Prosody: the rhythm and melody of speech - Timbre: what makes every voice unique - Coarticulation and why context matters - How all of this maps to AI TTS systems 🔬 WHY THIS MATTERS: Understanding human speech is essential for building realistic TTS. Modern neural vocoders and voice cloning models replicate these biological processes - the source-filter model directly informs how AI generates speech. CONSULTING: 🚀 AI Music + Audio Consulting: https://valeriovelardoadvisor.com/ 📩 Get my AI Music content in your inbox for free: https://valeriovelardo.substack.com/ COURSE MATERIALS + DISCUSSION: - GitHub Repository: https://github.com/musikalkemist/tts-voicecloning-course - Join The Sound of AI Slack Community: https://valeriovelardo.com/the-sound-of-ai-community/ (#tts-course channel) Content: 0:00 Intro 1:11 Human vs machine speech pipeline 3:32 Language 5:31 Phonemes 8:30 international Phonetic Alphabet 13:14 English phonetic chart 14:55 Phonetic transcription 16:20 Coarticulation 18:53 Prosody 21:34 Timbre 25:19 Source-fliter model of speech production 30:12 Glottal sound 33:01 More source-filter model 34:42 Formants 40:22 Emotion and expressivity 42:22 Speech is multilayered 44:35 Why is speech hard for machines?

Welcome to the most comprehensive Text-to-Speech (TTS) and Voice Cloning course on YouTube! Learn how AI systems generate realistic human speech from text. In this video, I outline the plan for the course and explain how to make the most out of it. 📚 WHAT YOU'LL LEARN: Foundations → Core Technologies (Neural Vocoders, Audio Codecs, Voice Cloning) → Advanced Topics (Emotion, Prosody, Conversational AI) 🎯 WHO THIS IS FOR: ML Engineers, Audio Programmers, Developers, Engineering Managers, Product Managers CONSULTING: 🚀 AI Music + Audio Consulting: https://valeriovelardoadvisor.com/ 📩 Get my AI Music content in your inbox for free: https://valeriovelardo.substack.com/ COURSE MATERIALS + DISCUSSION: - GitHub Repository: https://github.com/musikalkemist/tts-voicecloning-course - Join The Sound of AI Slack Community: https://valeriovelardo.com/the-sound-of-ai-community/ (#tts-course channel) Content: 0:00 Intro 4:35 Who's this course for? 5:19 Pre-requisites 7:53 Teaching style 12:04 What you'll learn 21:21 Learning material + feedback 23:47 How to get the most out of this course 26:30 Course pace

Watch the presentations of the 3rd Generative AI Music Workshop, organized by The Sound of AI in collaboration with the Music Technology Group. Participants present the AI music technologies they developed during the workshop. The workshop was held at University Pompeu Fabra in Barcelona in December 2024. 🚀 Music Tech Advisory: https://valeriovelardoadvisor.com/ 🌱 Generative AI Music Workshop: https://www.upf.edu/web/mtg/generative-music-ai-workshop 🎧 My new startup Transparent Audio: https://www.transparentaudio.ai/ ✍️ My Substack on tech & society: https://valeriovelardotechandsociety.substack.com/ Content: 0:00 Intro 0:54 Sonic Palette 8:22 Binary Star 13:27 The Hive 18:24 asdf (Working Title) 23:42 ChordChemists 27:44 Synaesthesia 33:23 Balkon 37:55 WavePlay 42:47 LocomIA ChoIA

Watch the concert of the 3rd Generative AI Music Workshop, organized by The Sound of AI in collaboration with the Music Technology Group. Participants perform using the AI music technologies they developed during the workshop. The workshop was held at University Pompeu Fabra in Barcelona in December 2024. 🚀 Music Tech Advisory: https://valeriovelardoadvisor.com/ 🌱 Generative AI Music Workshop: https://www.upf.edu/web/mtg/generative-music-ai-workshop 🎧 My new startup Transparent Audio: https://www.transparentaudio.ai/ ✍️ My Substack on tech & society: https://valeriovelardotechandsociety.substack.com/ Content: 0:00 Intro 2:03 Binary Star 12:04 Balkon 16:25 WavePlay 20:12 The Hive 25:44 ChordChemists 29:23 asdf (Working Title) 32:57 Synaesthesia 45:03 LocomIA ChoIA

After more than a year of silence, I’m finally back. In this video, I share what’s been happening in my personal and professional life, why I stopped publishing, and what you can expect from me and this channel going forward. I’ll also tell you about some exciting new projects I’ve been working on, like my book AI Music Revolution, my startup Transparent Audio, and my new Substack on tech & society. 🚀 Music Tech Startup Advisory: https://valeriovelardoadvisor.com/ 🎧 My new startup Transparent Audio: https://www.transparentaudio.ai/ ✍️ My Substack on tech & society: https://valeriovelardotechandsociety.substack.com/ Content: 0:00 Intro 1:02 Personal update 1:58 Workshop on Generative AI Music 3:45 Adjunct Professor of Gen AI Music at MTG 5:21 Writing AI Music Revolution 10:13 Substack on tech & society 10:50 Consultant out, advisor in 14:03 New startup: Transparent Audio 16:16 What next?

I introduce 5 open source generative music AI models. They are both in the symbolic and audio space. You can use them to streamline the development of your AI music systems. Interested in music AI consulting? https://thesoundofai.com/consulting.html Interested in music AI recruitment? https://thesoundofai.com/recruitment.html ====================================== MusicGen Website: https://ai.honu.io/papers/musicgen/ Github: https://github.com/facebookresearch/audiocraft/blob/main/docs/MUSICGEN.md MuseCoco Website: https://ai-muzic.github.io/musecoco/ Github: https://github.com/microsoft/muzic/tree/main/musecoco Museformer Website: https://ai-muzic.github.io/museformer/ Github: https://github.com/microsoft/muzic/tree/main/museformer RAVE Github: https://github.com/acids-ircam/RAVE MusicAgent Article: https://arxiv.org/pdf/2310.11954 Github: https://github.com/microsoft/muzic/tree/main/musicagent ====================================== Check The AI Leader's Blueprint website: https://the-sound-of-ai-academy.teachable.com/p/the-ai-leader-s-blueprint Become a Python ninja with my Advanced Python Programming course: https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming Connect with Valerio on LinkedIn: https://www.linkedin.com/in/valeriovelardo Follow Valerio on Twitter: https://twitter.com/musikalkemist ====================================== Content 0:00 Intro 1:08 MusicGen 6:36 MuseCoco 11:40 Museformer 16:37 RAVE 19:19 MusicAgent

I implemented an AI music critic. It turned out to be more funny than I expected. Interested in music AI advisorship? https://thesoundofai.com/consulting.html Interested in music AI recruitment? https://thesoundofai.com/recruitment.html Code of the AI music critic on GitHub: https://github.com/musikalkemist/ai-music-critic ====================================== Check The AI Leader's Blueprint website: https://the-sound-of-ai-academy.teachable.com/p/the-ai-leader-s-blueprint Become a Python ninja with my Advanced Python Programming course: https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming Connect with Valerio on LinkedIn: https://www.linkedin.com/in/valeriovelardo Follow Valerio on Twitter: https://twitter.com/musikalkemist ====================================== Content 0:00 Intro 0:50 Why building an AI critic 1:26 How humans judge music 2:58 How AI understands music 3:38 Designing the AI critic 3:51 Essentia 4:26 Implementation 7:48 Running musiccritic 9:08 AI critiques 22 by Taylor Swift 11:50 Differences between human and AI critic 12:56 How to improve the AI critic

80% of AI projects fail. Learn how to maximise your success using a proven AI project lifecycle, that emphasizes customer discovery, strategic planning, and iterative development. Check The AI Leader's Blueprint website: https://the-sound-of-ai-academy.teachable.com/p/the-ai-leader-s-blueprint ====================================== Interested in music AI advisorship? https://thesoundofai.com/consulting.html Interested in music AI recruitment? https://thesoundofai.com/recruitment.html Become a Python ninja with my Advanced Python Programming course: https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming Connect with Valerio on LinkedIn: https://www.linkedin.com/in/valeriovelardo Follow Valerio on Twitter: https://twitter.com/musikalkemist ====================================== Content 0:00 Intro 0:38 Challenges with AI projects 1:05 My mantra 1:28 Customer discovery 3:24 Planning 4:48 Iterative development 5:41 Proof of Concept 6:12 Minimum viable product 6:44 The AI Leader's Blueprint 8:18 Full product 8:58 AI lifecycle in a nutshell

OpenAI released Sora, a state-of-the-art text-to-video deep learning model. In this video, I provide a complete breakdown of Sora. You can learn what Sora can do, how it works, its limitations, its emergent properties, its impact, and the safety threats it brings. Check The AI Leader's Blueprint website: https://the-sound-of-ai-academy.teachable.com/p/the-ai-leader-s-blueprint ====================================== Interested in music AI consulting? https://thesoundofai.com/consulting.html Interested in music AI recruitment? https://thesoundofai.com/recruitment.html Become a Python ninja with my Advanced Python Programming course: https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming Connect with Valerio on LinkedIn: https://www.linkedin.com/in/valeriovelardo Follow Valerio on Twitter: https://twitter.com/musikalkemist ====================================== Content 0:00 Intro 1:12 10K-foot overview 2:21 Use cases 4:17 How it works 11:10 The AI Leader's Blueprint 12:23 Emerging properties 17:24 Is Sora a world model? 21:49 Limitations 23:59 Impact 28:02 Safety 29:30 Ethical problems

"The AI Leader's Blueprint" is a 3-day crash course on Zoom that helps you become an AI leader. Check The AI Leader's Blueprint website: https://the-sound-of-ai-academy.teachable.com/p/the-ai-leader-s-blueprint ====================================== Interested in music AI consulting? https://thesoundofai.com/consulting.html Interested in music AI recruitment? https://thesoundofai.com/recruitment.html Become a Python ninja with my Advanced Python Programming course: https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming Connect with Valerio on LinkedIn: https://www.linkedin.com/in/valeriovelardo Follow Valerio on Twitter: https://twitter.com/musikalkemist ====================================== Content 0:00 The AI Leader's Blueprint 0:43 What it takes to be an AI leader 2:17 Course focus 3:06 Who's the course for? 3:35 Teaching style 4:23 Course schedule 4:45 Course website 5:37 What you'll learn 8:45 Why should you attend this course? 10:25 Student's feedback 11:33 What you'll get

Learn about text-to-music generation with Mustango. Get the lecture slides: https://github.com/musikalkemist/generativemusicaicourse/blob/main/22.%20Text-to-music%20generation%20with%20Mustango/Slides/22.%20Text-to-music%20generation%20with%20Mustango.pdf Iran's YouTube channel: https://www.youtube.com/@iran-r-roman/videos Website of the Generative Music AI Workshop in Barcelona: https://www.upf.edu/web/mtg/generative-music-ai-workshop Sign up to The Sound of AI Slack Community to join the discussion: https://valeriovelardo.com/the-sound-of-ai-community/ ====================================== Interested in music AI consulting? https://thesoundofai.com/consulting.html Interested in music AI recruitment? https://thesoundofai.com/recruitment.html Become a Python ninja with my Advanced Python Programming course: https://the-sound-of-ai-academy.teachable.com/p/advanced-python-programming Connect with Valerio on LinkedIn: https://www.linkedin.com/in/valeriovelardo Follow Valerio on Twitter: https://twitter.com/musikalkemist ====================================== Content 0:00 Intro 1:00 MusicBench dataset 6:10 Architecture 9:34 Sample generated music 13:48 Generating music with a prompt 17:44 A word from Valerio