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Manila Kodali
Manila Kodali
Doctoral Researcher, Aalto University
在 aalto.fi 的电子邮件经过验证
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引用次数
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Wav2vec-based detection and severity level classification of dysarthria from speech
F Javanmardi, S Tirronen, M Kodali, SR Kadiri, P Alku
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
162023
Motion pattern recognition in 4d point clouds
D Salami, S Palipana, M Kodali, S Sigg
2020 IEEE 30th International Workshop on Machine Learning for Signal …, 2020
132020
Comparing 1-dimensional and 2-dimensional spectral feature representations in voice pathology detection using machine learning and deep learning classifiers
F Javanmardi, S Kadiri, M Kodali, P Alku
Interspeech, 2173-2177, 2022
122022
Utilizing wav2vec in database-independent voice disorder detection
S Tirronen, F Javanmardi, M Kodali, SR Kadiri, P Alku
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
92023
Classification of vocal intensity category from speech using the wav2vec2 and whisper embeddings
M Kodali, S Kadiri, P Alku
Interspeech, 4134-4138, 2023
52023
Automatic classification of vocal intensity category from speech
M Kodali, SR Kadiri, L Laaksonen, P Alku
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
32023
Automatic classification of the severity level of Parkinson’s disease: A comparison of speaking tasks, features, and classifiers
M Kodali, SR Kadiri, P Alku
Computer Speech & Language 83, 101548, 2023
22023
Automatic classification of vocal intensity category from speech
M Kodali
22021
Towards battery-less RF sensing
M Kodali, S Sigg
2021 IEEE International Conference on Pervasive Computing and Communications …, 2021
12021
AVID: A speech database for machine learning studies on vocal intensity
P Alku, M Kodali, L Laaksonen, SR Kadiri
Speech Communication 157, 103039, 2024
2024
Investigating fine-tuning of pre-trained models for classification of vocal intensity category from speech signals
M Kodali, S Kadiri, P Alku
Proceedings of Interspeech'24, 2024
2024
Severity classification of Parkinson's disease from speech using single frequency filtering-based features
SR Kadiri, M Kodali, P Alku
arXiv preprint arXiv:2308.09042, 2023
2023
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