Papers with Automatic speech recognition systems
Improving End-to-End Bangla Speech Recognition with Semi-supervised Training (2020.findings-emnlp)
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| Challenge: | Existing methods to train speech recognition systems require large annotated corpus. |
| Approach: | They propose a semi-supervised training approach that exploits large unpaired audio and text data to improve the performance of an automatic speech recognition system. |
| Outcome: | The proposed method reduces the WER of the system from 37% to 31.9%. |
Evaluating Automatic Speech Recognition Systems for Korean Meteorological Experts (2025.findings-emnlp)
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| Challenge: | Using a dataset of Korean weather queries, we find that automatic speech recognition systems fail on specialized vocabulary. |
| Approach: | They propose an evaluation dataset of Korean weather queries . the dataset was recorded by diverse native speakers following pronunciation guidelines . |
| Outcome: | The proposed model reduces error rates on meteorological terms and improves overall recognition accuracy. |
Preparation of Bangla Speech Corpus from Publicly Available Audio & Text (2020.lrec-1)
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Shafayat Ahmed, Nafis Sadeq, Sudipta Saha Shubha, Md. Nahidul Islam, Muhammad Abdullah Adnan, Mohammad Zuberul Islam
| Challenge: | Automated speech recognition systems require large annotated speech corpus for training. |
| Approach: | They propose to use publicly available Bangla audiobooks and TV news recordings as input to prepare a large speech corpus with reasonable confidence. |
| Outcome: | The proposed algorithm outperforms the existing speech corpus and the existing corpus with speaker diarization and gender detection. |