Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
19 Hour(s) 30 Minute(s)
Language
English
Taught by
Vinit Singh
Rating
Course Overview
Master cutting-edge SpeechLMs and build next-generation voice AI applications with end-to-end speech capabilities
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.
What You'll Master:
Speech Language Models represent the next frontier in AI, moving beyond the limitations of traditional ASR→LLM→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.
Why This Course Matters:
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.
What Makes This Course Unique:
Hands-on Learning: Work with state-of-the-art models like YourTTS, Whisper, and HuBERT
Complete Pipeline Coverage: From raw audio to deployed applications
Real-world Applications: Build ASR systems, voice cloning, emotion recognition, and interactive voice agents
Latest Research: Covers cutting-edge developments in the rapidly evolving SLM field
Practical Implementation: Learn training methodologies, evaluation metrics, and deployment strategies
Key Technologies You'll Work With:
Speech tokenizers (EnCodec, HuBERT, Wav2Vec 2.0)
Transformer architectures adapted for speech (Whisper , Conformer models etc)
Vocoder technologies (Tacotron, Hi-Fi GAN, MelGAN etc)
Multi-modal training approaches (CTC, UCTC etc
Parameter-efficient fine-tuning (LoRA)
Perfect For:
AI/ML engineers wanting to specialize in speech technology
Students or Career Changers
Researchers exploring next-generation voice AI
Developers building voice-first applications
Anyone curious about how modern voice assistants really work
Course Outcome:
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. You'll understand both the theoretical foundations and practical implementation details needed to contribute to this exciting field.
Join the voice AI revolution and master the technology that's reshaping human-computer interaction!
Course Content
- 8 section(s)
- 111 lecture(s)
- Section 1 Introduction
- Section 2 Module 1: Introduction to Speech Language Processing and the Emergence of Speech
- Section 3 Module 2: Fundamentals of Speech and Language for SpeechLMs
- Section 4 Module 3: Architectures and Key Components of SpeechLMs
- Section 5 Module 4: Training Methodologies for SpeechLMs
- Section 6 Module 5: Capabilities and Applications of SpeechLMs in Detail
- Section 7 Module 6: Evaluation Metrics and Benchmarking of SpeechLMs
- Section 8 Module 7: Challenges and Future Directions in SpeechLM Research
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.
Skills covered in this course
Reviews
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PPradeep Kumar
very good
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AAkash Shetti
The course covers fundamentals of speech processing. I liked the course structure as well.
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SShreya Singh
This course was very beneficial to me as a student and working professional who wanted to learn AI. The ideas are well elaborated using simple words that render learning simple and interesting. The presentation is also well-organized, which simplifies the complex aspects of AI significantly. A must recommended to all people beginning their AI journey!
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NNiraj
The thing I liked most is that each theory lecture is followed by a Coding example. This helps in applying what is learnt. Also there is coding exercise also that further solidifies the fundamentals
