Decoding Language Discriminative Features In EEG Signals
Abstract:
This project presents an experimental study to probe the language discriminative cues in neural responses to speech stimuli presented from two languages. In this study using electroencephalography (EEG) recordings, one of the first ones in this direction, we explore the differences in human perception while listening to a familiar and an unfamiliar language. The main objective of this study is to analyze the changes in brain responses when a human subject is listening under familiar and foreign conditions in a linguistic sense. The stimuli-set for this study contains words from English (familiar language) and from Japanese (unfamiliar language). The language discriminative representations are probed by designing an off-line language classifier on the EEG signals. These experiments reveal that the time-frequency representations along with the phase information of EEG signal carry significant language discriminative information. We obtain an average accuracy of 64.4% among 12 subjects with a support vector machine based classifier, which is significantly above chance.
An EEG-based Study On the Evolution of Brain Representations during Language Learning
Abstract:
The early stages of language learning consists of learning new words from an unfamiliar language through phases of listening and articulating the words of the language over time. In this study, we design an experimental setup to understand the evolution of neural representations in a language learning task. The human subjects in the experiment are performing the task of listening and reproducing a set of words from a familiar language (English) and an unfamiliar language (Japanese). During the task, electroencephalogram (EEG) signals are recorded in addition to the spoken audio signals. With a detailed analysis on the recorded EEG signals and the audio signals, we propose to uncover the language learning process by highlighting the difference between these signals for the known and the unknown language. Upon exposure to multiple trials of the same word from the unfamiliar language, we find that the inter-trial distance between EEG signals (as well as the spoken audio signals) decreases, indicating a consistency in the neural representations. In addition, the brain regions (in terms of EEG channel locations) responsible for the learning task are identified.
ERP Evidences of Rapid Semantic Learning of Foreign Language Words
Abstract:
The event related potential (ERP) based analysis of electroencephalography (EEG) signals has been well studied in the case of native language stimuli using semantically matched and mis-matched end-words. For example, the presence of N400 component in the ERP has been shown to indicate semantic mis-match. However, it is unclear whether the semantic dissimilarity effects in ERP also appear for foreign language words that were learned in a rapid language learning task. In this study, the first of its kind, we introduce the semantics of Japanese words to subjects (who had no prior exposure to Japanese). Following this language learning task, we perform ERP analysis using English sentences of semantically matched and mis-matched nature where the end-words are replaced with their Japanese counterparts. The ERP analysis reveals that, even with a short learning cycle, the semantically matched and mis-matched stimuli elicit different EEG patterns (similar to the native language case). However, the patterns seen for the Japanese stimuli show the presence of P400 component (opposite in polarity to those seen in the native language). A topographical analysis reveals that the brain regions that are involved in generating these P400 responses pre-dominantly in the parietal region.
The audio files of the stimuli used in this experiment can be found here.
The link to word detection experiment can be found here.
Publications

  • A. Soman, Madhavan C. R., K. Sarkar, and S. Ganapathy, "An EEG Study On The Brain Representations in Language Learning", IOP Journal on Biomedical Physics and Engineering Express, 5(2), 25041, (2019).

  • K. Praveen, A. Gupta, A. Soman and S. Ganapathy "Second Language Transfer Learning in Humans and Machines Using Image Supervision", IEEE ASRU, Dec. 2019.

  • V. Krishnamohan, A. Soman, A. Gupta and S. Ganapathy,"Audiovisual Correspondence Learning in Humans And Machines", Interspeech 2020, Beijing, October 2020.
  • A. Soman, P. Ramachandran, and S. Ganapathy, " ERP Evidences of Rapid Semantic Learning In Foreign Language Word Comprehension ," Frontiers in Neuroscience, 2022. [Data]
  • Office: LEAP Lab (C328) / aksharas AT iisc DOT ac DOT in / 080-2293-2362
    Postal: C328 (LEAP Lab) / Department of Electrical Engineering / IISc Bangalore / India 560012