Deep Learning Methods for EEG-Based Speech Classification and Decoding: A PRISMA Review
We are pleased to share that Asma Sbaih, together with Jorge García-Gutiérrez, Megha Bhushan and David Benavides, has published a new article entitled "Deep Learning Methods for EEG-Based Speech Classification and Decoding: A PRISMA Review", now available in open access in Computer Speech & Language (Elsevier).The article presents a systematic review, conducted following the PRISMA 2020 guidelines, of deep learning methods applied to speech-related EEG (electroencephalography) and intracranial EEG (iEEG) processing, covering studies published between 2018 and 2025. After searching across Scopus, IEEE Xplore, ScienceDirect, Web of Science and PubMed, the authors identified 1,148 records, of which 80 peer-reviewed studies were included following duplicate removal, screening and eligibility assessment.The review organizes the literature by task type (speech classification, spectrogram reconstruction and speech synthesis), neural signal type (non-invasive EEG versus invasive…