New Baseline in Automatic Speech Recognition for Northern Sámi
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Professional
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In this paper, we show that these techniques are capable of yielding improvements even in a small data scenario. We experiment with different deep neural network architectures for acoustic modeling for Northern Sámi, and report up to 50% relative error rate reductions.
We also run experiments to compare the performance of different subwords as language modeling units in Northern Sámi.
|Title of host publication||Fourth International Workshop on Computational Linguistics for Uralic Languages|
|Publication status||Published - 2017|
|MoE publication type||D3 Professional conference proceedings|
|Event||International Workshop on Computational Linguistics for the Uralic Languages - Helsinki, Finland|
Duration: 8 Jan 2018 → 9 Jan 2018
Conference number: 4
|Conference||International Workshop on Computational Linguistics for the Uralic Languages|
|Period||08/01/2018 → 09/01/2018|