Papers with Convolution Neural Network
Transfer Learning Based Free-Form Speech Command Classification for Low-Resource Languages (P19-2)
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| Challenge: | Current speech-based user interfaces use data intensive methodologies to recognize free-form speech commands, but this is not viable for low-resource languages, which lack speech data. |
| Approach: | They propose a method to develop a domain-specific speech command classification system using speech data from a high-resource language. |
| Outcome: | The proposed system is robust to low-resource languages with limited speech data . the proposed system achieves significant results for Sinhala and Tamil datasets . |
Deep Learning against COVID-19: Respiratory Insufficiency Detection in Brazilian Portuguese Speech (2021.findings-acl)
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Edresson Casanova, Lucas Gris, Augusto Camargo, Daniel da Silva, Murilo Gazzola, Ester Sabino, Anna Levin, Arnaldo Candido Jr, Sandra Aluisio, Marcelo Finger
| Challenge: | Respiratory insufficiency is a symptom that requires hospitalization . a dataset was created to analyze COVID-19 patients and a control group . |
| Approach: | They used a dataset to build a Convolution Neural Network to detect respiratory insufficiency using MFCC representations. |
| Outcome: | The proposed method achieves 91.66% accuracy under real-life environmental conditions. |
Finnish Hate-Speech Detection on Social Media Using CNN and FinBERT (2022.lrec-1)
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| Challenge: | Existing tools to identify hate posts from social media are limited in the field of online hate speech detection. |
| Approach: | They propose to use finBERT to generate a Finnish hate speech dataset . finBERt has a 91.7% accuracy and 90.8% F1 score value, they say . |
| Outcome: | The proposed model outperforms state-of-the-art models in Finnish and other languages. |