1 code implementation • 4 Oct 2023 • Daniel Mann, Tina Raissi, Wilfried Michel, Ralf Schlüter, Hermann Ney
We investigate recognition results and additionally Viterbi alignments of our models.
no code implementations • 24 Oct 2022 • Christoph Lüscher, Mohammad Zeineldeen, Zijian Yang, Tina Raissi, Peter Vieting, Khai Le-Duc, Weiyue Wang, Ralf Schlüter, Hermann Ney
Language barriers present a great challenge in our increasingly connected and global world.
no code implementations • 11 Dec 2020 • Valentin Mendelev, Tina Raissi, Guglielmo Camporese, Manuel Giollo
Automatic Speech Recognition (ASR) based on Recurrent Neural Network Transducers (RNN-T) is gaining interest in the speech community.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 15 May 2020 • Tina Raissi, Eugen Beck, Ralf Schlüter, Hermann Ney
In this work, we address a direct phonetic context modeling for the hybrid deep neural network (DNN)/HMM, that does not build on any phone clustering algorithm for the determination of the HMM state inventory.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • 15 Nov 2019 • Tina Raissi, Santiago Pascual, Maurizio Omologo
The candidate time windows are selected from a set of large time intervals, possibly including a sample drop, and by using a preprocessing step.
Sound Audio and Speech Processing I.2.7
no code implementations • 12 May 2018 • Tina Raissi, Alessandro Tibo, Paolo Bientinesi
We present a feature engineering pipeline for the construction of musical signal characteristics, to be used for the design of a supervised model for musical genre identification.