Description
Mastering Generative Voice AI: From Tokens to Agentic TTS. Generative voice AI goes far beyond simple text-to-speech, and this course takes you from the fundamentals of voice physics to building intelligent, production-level voice systems. Most text-to-speech courses are limited to basic models or ready-made programming interfaces, but this course goes much deeper. Participants will first learn the fundamentals of human speech, including acoustics, lexicon, and intonation, and then explore advanced architectures of today’s voice models, such as self-supervised representation learning, neural voice codecs, and tokenization strategies that allow large language models to speak. Students will then master two popular modern paradigms—autoregressive codec-based text-to-speech and hidden propagation or conditional stream matching—and understand when and why each is used in real-world systems. Integrated audio and text models, paralinguistic modeling, and zero-shot voice simulation are also explored. The final sections teach how to build agent-based, streaming, and low-latency audio pipelines, including segmented inference, speculative decoding, websocket streaming, and speech turn management.
What you will learn
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Understanding the science of speech production and acoustic feature extraction
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Comparing traditional pipelines with modern speech language model architectures
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Construction and application of neural audio codecs and semantic markup
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Implementing codec-based autoregressive text-to-speech conversion
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Designing integrated audio and text models with multi-modal alignment
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Applying latent diffusion and conditional flow matching to produce high-quality spectrograms
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Evaluating the advantages and disadvantages of stream matching versus diffusion
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Deploying smart, streaming audio systems with real-time outage management capabilities
This course is suitable for people who:
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Machine learning and artificial intelligence engineers who want to go beyond calling programming interfaces and understand the inner workings of advanced audio models.
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Researchers in the field of natural language and speech processing who seek to bridge classical signal processing with modern generative modeling.
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Voice technology founders and product engineers who build conversational AI agents need to make informed architectural decisions.
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Graduate students or self-taught machine learning professionals looking for a rigorous and comprehensive training program in the field of generative audio.
Course Details: Mastering Generative Voice AI: From Tokens to Agentic TTS
- Publisher: Udemy
- Instructor: Vinit Singh
- Training level: Beginner to advanced
- Training duration: 33 hours and 1 minute
- Number of lessons: 374
Course syllabus for 2026/7
Prerequisites for the Mastering Generative Voice AI: From Tokens to Agentic TTS course
- A solid understanding of deep learning fundamentals (neural networks, backpropagation, and training basics)
- Working knowledge of Python and a deep learning framework such as PyTorch
- Basic familiarity with core NLP or LLM concepts (tokenization, transformers, attention) is helpful but not mandatory — key ideas are reviewed in the course
- No prior audio signal processing experience needed — Module 1 builds this from first principles
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
16.4 GB
