15 citations · 16 across the 5 of their papers we have counts for
5 papers
End-to-end Ensemble-based Feature Selection for Paralinguistics Tasks
Tamás Grósz, Mittul Singh, Sudarsana Reddy Kadiri +2
The events of recent years have highlighted the importance of telemedicine solutions which could potentially allow remote treatment and diagnosis. Relatedly, Computational Paraling…
Comparison and Analysis of New Curriculum Criteria for End-to-End ASR
Georgios Karakasidis, Tamás Grósz, Mikko Kurimo
It is common knowledge that the quantity and quality of the training data play a significant role in the creation of a good machine learning model. In this paper, we take it one st…
Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks
Anssi Moisio, Dejan Porjazovski, Aku Rouhe +5
The Donate Speech campaign has so far succeeded in gathering approximately 3600 hours of ordinary, colloquial Finnish speech into the Lahjoita puhetta (Donate Speech) corpus. The c…
Data augmentation using prosody and false starts to recognize non-native children's speech
Hemant Kathania, Mittul Singh, Tamás Grósz +1
This paper describes AaltoASR's speech recognition system for the INTERSPEECH 2020 shared task on Automatic Speech Recognition (ASR) for non-native children's speech. The task is t…
Aalto's End-to-End DNN systems for the INTERSPEECH 2020 Computational Paralinguistics Challenge
Tamás Grósz, Mittul Singh, Sudarsana Reddy Kadiri +2
End-to-end neural network models (E2E) have shown significant performance benefits on different INTERSPEECH ComParE tasks. Prior work has applied either a single instance of an E2E…