Value-Added Program (VAP) : Bridging Text and Speech-Practical Foundations in NLP and Speech Processing

About the Program

This program is designed to provide participants with a strong foundation in Natural Language Processing (NLP) and Speech Processing, two rapidly growing domains in artificial intelligence. It focuses on practical applications such as text analysis, sentiment detection, speech recognition, and conversational AI. Through hands-on training, case studies, and tool-based learning, students will gain insights into how machines process human language and voice. The program aims to bridge theoretical concepts with real-world implementations, preparing learners for research and industry roles in AI-driven communication technologies.

Objectives of the Program

• Understand the fundamentals of Natural Language Processing (NLP) and Speech Processing, along with their real-world applications.
• Apply text preprocessing techniques (tokenization, stemming, lemmatization, stopword removal, POS tagging) using Python NLTK.
• Analyze text corpora using feature extraction methods such as Bag-of-Words, TF-IDF, and N-grams for building NLP models.
• Develop basic NLP applications such as sentiment analysis, named entity recognition, and text summarization.
• Explore the basics of speech signal representation, feature extraction (MFCCs, spectrograms), and speech-to-text processing.
• Integrate speech and text processing into simple real-world applications such as voice-based sentiment analysis or speech-driven chatbots.

Expected Outcomes of the Program

• Explain the concepts of NLP pipelines and speech processing workflows.
• Implement text preprocessing and corpus analysis using Python NLTK.
• Design and implement simple speech-to-text applications and integrate them with NLP models.