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code availability eeg data analyses  (MathWorks Inc)


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    MathWorks Inc code availability eeg data analyses
    Fig. 1. AAD framework and speech envelope in continuous Mandarin speech. (a) Speech envelopes for two example sentences (transcript in Chinese and Pinyin) spoken by a native Mandarin speaker. (b) AAD framework for Mandarin speech. According to the oscillation rhythm, <t>EEG</t> signals were divided into the low-frequency band (0.1–15 Hz) and beta-band (15–30 Hz). We used the low-frequency band and whole rhythm (0.1–30 Hz) for AAD. 60-channel of the whole-brain and optimized 17-channel (mainly including STG and Prefrontal lobe) <t>EEG</t> <t>data</t> were used to reconstruct the speech envelope based on the LSTM model. The correlation analysis was carried out according to the reconstructed envelope and the speech envelope of multiple speech sources. The most relevant speech was determined as the subject of attention.
    Code Availability Eeg Data Analyses, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2255 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    code availability eeg data analyses - by Bioz Stars, 2026-03
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    1) Product Images from "Auditory attention decoding from EEG-based Mandarin speech envelope reconstruction."

    Article Title: Auditory attention decoding from EEG-based Mandarin speech envelope reconstruction.

    Journal: Hearing research

    doi: 10.1016/j.heares.2022.108552

    Fig. 1. AAD framework and speech envelope in continuous Mandarin speech. (a) Speech envelopes for two example sentences (transcript in Chinese and Pinyin) spoken by a native Mandarin speaker. (b) AAD framework for Mandarin speech. According to the oscillation rhythm, EEG signals were divided into the low-frequency band (0.1–15 Hz) and beta-band (15–30 Hz). We used the low-frequency band and whole rhythm (0.1–30 Hz) for AAD. 60-channel of the whole-brain and optimized 17-channel (mainly including STG and Prefrontal lobe) EEG data were used to reconstruct the speech envelope based on the LSTM model. The correlation analysis was carried out according to the reconstructed envelope and the speech envelope of multiple speech sources. The most relevant speech was determined as the subject of attention.
    Figure Legend Snippet: Fig. 1. AAD framework and speech envelope in continuous Mandarin speech. (a) Speech envelopes for two example sentences (transcript in Chinese and Pinyin) spoken by a native Mandarin speaker. (b) AAD framework for Mandarin speech. According to the oscillation rhythm, EEG signals were divided into the low-frequency band (0.1–15 Hz) and beta-band (15–30 Hz). We used the low-frequency band and whole rhythm (0.1–30 Hz) for AAD. 60-channel of the whole-brain and optimized 17-channel (mainly including STG and Prefrontal lobe) EEG data were used to reconstruct the speech envelope based on the LSTM model. The correlation analysis was carried out according to the reconstructed envelope and the speech envelope of multiple speech sources. The most relevant speech was determined as the subject of attention.

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    code availability eeg data analyses  (MathWorks Inc)
    96
    MathWorks Inc code availability eeg data analyses
    Fig. 1. AAD framework and speech envelope in continuous Mandarin speech. (a) Speech envelopes for two example sentences (transcript in Chinese and Pinyin) spoken by a native Mandarin speaker. (b) AAD framework for Mandarin speech. According to the oscillation rhythm, <t>EEG</t> signals were divided into the low-frequency band (0.1–15 Hz) and beta-band (15–30 Hz). We used the low-frequency band and whole rhythm (0.1–30 Hz) for AAD. 60-channel of the whole-brain and optimized 17-channel (mainly including STG and Prefrontal lobe) <t>EEG</t> <t>data</t> were used to reconstruct the speech envelope based on the LSTM model. The correlation analysis was carried out according to the reconstructed envelope and the speech envelope of multiple speech sources. The most relevant speech was determined as the subject of attention.
    Code Availability Eeg Data Analyses, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/code availability eeg data analyses/product/MathWorks Inc
    Average 96 stars, based on 1 article reviews
    code availability eeg data analyses - by Bioz Stars, 2026-03
    96/100 stars
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    Fig. 1. AAD framework and speech envelope in continuous Mandarin speech. (a) Speech envelopes for two example sentences (transcript in Chinese and Pinyin) spoken by a native Mandarin speaker. (b) AAD framework for Mandarin speech. According to the oscillation rhythm, EEG signals were divided into the low-frequency band (0.1–15 Hz) and beta-band (15–30 Hz). We used the low-frequency band and whole rhythm (0.1–30 Hz) for AAD. 60-channel of the whole-brain and optimized 17-channel (mainly including STG and Prefrontal lobe) EEG data were used to reconstruct the speech envelope based on the LSTM model. The correlation analysis was carried out according to the reconstructed envelope and the speech envelope of multiple speech sources. The most relevant speech was determined as the subject of attention.

    Journal: Hearing research

    Article Title: Auditory attention decoding from EEG-based Mandarin speech envelope reconstruction.

    doi: 10.1016/j.heares.2022.108552

    Figure Lengend Snippet: Fig. 1. AAD framework and speech envelope in continuous Mandarin speech. (a) Speech envelopes for two example sentences (transcript in Chinese and Pinyin) spoken by a native Mandarin speaker. (b) AAD framework for Mandarin speech. According to the oscillation rhythm, EEG signals were divided into the low-frequency band (0.1–15 Hz) and beta-band (15–30 Hz). We used the low-frequency band and whole rhythm (0.1–30 Hz) for AAD. 60-channel of the whole-brain and optimized 17-channel (mainly including STG and Prefrontal lobe) EEG data were used to reconstruct the speech envelope based on the LSTM model. The correlation analysis was carried out according to the reconstructed envelope and the speech envelope of multiple speech sources. The most relevant speech was determined as the subject of attention.

    Article Snippet: Our work chieved an accuracy of 74.29% within a 0.15 s decision window, hich may provide a strong practical application in hearing aids. urthermore, the architecture could help develop neuro-steered earing devices, especially those who speak tonal languages. ata and code availability EEG data analyses were performed in MATLAB, the freely availble toolbox EEGLAB, and Python 3.8.

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