Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition
In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) features recorded synchronously with aphasia, apraxia, and dysarthria speech. We demonstrate a significant decoding performance improvement by more than 50\% during test time for isolated speech recognition task and we also provide preliminary results indicating performance improvement for the more challenging continuous speech recognition task by utilizing EEG features. The results presented in this paper show the first step towards demonstrating the possibility of utilizing non-invasive neural signals to design a real-time robust speech prosthetic for stroke survivors recovering from aphasia, apraxia, and dysarthria. Our aphasia, apraxia, and dysarthria speech-EEG data set will be released to the public to help further advance this interesting and crucial research.
Code (0)
등록된 구현이 없습니다.
Tasks
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)EEGElectroencephalogram (EEG)speech-recognitionSpeech RecognitionSimilar Papers 제목 키워드 기반
Prosody of speech production in latent post-stroke aphasia
This study explores prosodic production in latent aphasia, a mild form of aphasia associated with left-hemisphere brain damage (e.g. stroke). Unlike prior research on moderate to severe aphasia, we investigated latent ap…
DiagnosticTowards a Method for Synthetic Generation of Persons with Aphasia Transcripts
In aphasia research, Speech-Language Pathologists (SLPs) devote extensive time to manually coding speech samples using Correct Information Units (CIUs), a measure of how informative an individual sample of speech is. Dev…
Learning Co-Speech Gesture for Multimodal Aphasia Type Detection
Aphasia, a language disorder resulting from brain damage, requires accurate identification of specific aphasia types, such as Broca's and Wernicke's aphasia, for effective treatment. However, little attention has been pa…
Graph Neural NetworkUnsupervised Paraphasia Classification in Aphasic Speech
Aphasia is a speech and language disorder which results from brain damage, often characterized by word retrieval deficit (anomia) resulting in naming errors (paraphasia). Automatic paraphasia detection has many benefits …
ClassificationGeneral ClassificationRetrievalTransfer LearningArtificial Aphasias in Lesioned Language Models
Aphasias, selective language impairments which can arise from brain damage, reveal the functional organization of human language by providing causal links between affected brain regions and specific symptom profiles. Dra…