Practical Solutions for Diverse Real-World NLP Applications (Signals and Communication Technology)

This book unveils the most advanced techniques and innovative applications in the natural language processing (NLP) field. It uncovers the secrets to enhancing language understanding, and presents practical solutions to different NLP tasks, as text augmentation, paraphrase generation, and restoring spaces and punctuation in multiple languages. It unlocks the potential of hierarchical multi-task learning for cross-lingual phoneme recognition, and allows readers to explore more real-world applications such as error correction, aggregating industrial security findings as well as predicting music emotion values from social media conversations. "Practical Solutions for Diverse Real-World NLP Applications" is the suitable guidebook for researchers, students, and practitioners as it paves the way for them by delivering invaluable insights and knowledge.

Dr. Mourad Abbas is research director at the High Council of Arabic, specializing in the dynamic field of natural language processing with a primary focus on the Arabic language and its diverse dialects. With a passion for pushing the boundaries of NLP, Dr. Abbas' research interests span a wide range of crucial topics, including machine translation, speech recognition, language identification, natural language understanding, and the challenges faced by under-resourced languages.

Throughout his career, Dr. Abbas has made many contributions to the academic community, having published over sixty impactful papers. He has also played an important role in editing the proceedings of renowned conferences and workshops such as ICNLSP and NSURL, featured in prestigious platforms like Elsevier, ACL Anthology, and IEEExplore.

Recognized as an expert in his field, Dr. Abbas is actively engaged in peer review activities for distinguished journals, such as Language Resources and Evaluation, and Digital Signal Processing, along with conferences like ICASSP, Interspeech, Coling, and NAACL-HLT.