Descriptions
Mastering Voice AI : From ASR to Emotion AI to Voice Cloning, Transform your understanding of voice AI with this comprehensive course on Speech Language Models (SLMs) – the revolutionary technology that’s replacing traditional speech processing pipelines with powerful end-to-end solutions. Speech Language Models represent the next frontier in AI, moving beyond the limitations of traditional ASR, LLM, and TTS pipelines. This course takes you from fundamental concepts to advanced applications, covering everything from speech tokenization and transformer architectures to emotion AI and real-time voice interactions. Traditional speech processing suffers from information loss, high latency, and error accumulation across multiple stages. SLMs solve these problems by processing speech directly, capturing not just words but emotions, speaker identity, and paralinguistic cues that make human communication rich and nuanced. You will work hands-on with state-of-the-art models like YourTTS, Whisper, and HuBERT, covering the complete pipeline from raw audio to deployed applications. Build ASR systems, voice cloning, emotion recognition, and interactive voice agents, and learn about the latest research and practical implementation strategies. Key technologies include speech tokenizers (EnCodec, HuBERT, Wav2Vec 2.0), transformer architectures for speech (Whisper, Conformer), vocoder technologies (Tacotron, Hi-Fi GAN, MelGAN), multi-modal training approaches (CTC, UCTC), and parameter-efficient fine-tuning (LoRA). This course is perfect for AI/ML engineers, students, researchers, developers, and anyone curious about modern voice assistants. By completion, you’ll have the skills to design, train, and deploy Speech Language Models for diverse applications, from basic speech recognition to sophisticated emotion-aware voice agents, understanding both theoretical foundations and practical implementation.
What you’ll learn
- Develop end-to-end speech language models using Python and Transformer architectures.
- Master audio feature extraction and tokenization for speech recognition and synthesis.
- Build AI for emotion recognition and personalized speech with real-world applications.
- Evaluate SpeechLMs with metrics like WER and explore ethical AI design practices.
Who this course is for
- This course is for aspiring AI developers, data scientists, and tech enthusiasts eager to pioneer the future of voice AI with Speech Language Models.
- Perfect for beginners with basic Python and ML skills, as well as intermediate learners aiming to build advanced applications like real-time speech recognition, emotion-aware voice assistants, and speech translation.
- Unlock the power of end-to-end speech processing for cutting-edge careers in AI!
Specificatoin of Mastering Voice AI : From ASR to Emotion AI to Voice Cloning
- Publisher : Udemy
- Teacher : Vinit Singh
- Language : English
- Level : All Levels
- Number of Course : 111
- Duration : 19 hours and 30 minutes
Content of Mastering Voice AI : From ASR to Emotion AI to Voice Cloning
Requirements
- No prior speech AI experience required beginner-friendly with hands-on guidance!
- A computer with Python 3.7+, TensorFlow/PyTorch, and audio libraries (e.g., Librosa).
- Basic Python programming (familiarity with loops, functions, and libraries like NumPy).
Pictures
Sample Clip
Installation Guide
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Subtitle : English
Quality: 720
Download Links
Downloadly
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Password file(s): www.downloadly.ir
File size
5.33 GB
