1 citations · 1 across the 3 of their papers we have counts for
6 papers
Dialect Adaptation and Data Augmentation for Low-Resource ASR: TalTech Systems for the MADASR 2023 Challenge
Tanel Alumäe, Jiaming Kong, Daniil Robnikov
This paper describes Tallinn University of Technology (TalTech) systems developed for the ASRU MADASR 2023 Challenge. The challenge focuses on automatic speech recognition of diale…
Collar-aware Training for Streaming Speaker Change Detection in Broadcast Speech
Joonas Kalda, Tanel Alumäe
In this paper, we present a novel training method for speaker change detection models. Speaker change detection is often viewed as a binary sequence labelling problem. The main cha…
Pretraining Approaches for Spoken Language Recognition: TalTech Submission to the OLR 2021 Challenge
Tanel Alumäe, Kunnar Kukk
This paper investigates different pretraining approaches to spoken language identification. The paper is based on our submission to the Oriental Language Recognition 2021 Challenge…
VoxLingua107: a Dataset for Spoken Language Recognition
Jörgen Valk, Tanel Alumäe
This paper investigates the use of automatically collected web audio data for the task of spoken language recognition. We generate semi-random search phrases from language-specific…
Weakly Supervised Training of Speaker Identification Models
Martin Karu, Tanel Alumäe
We propose an approach for training speaker identification models in a weakly supervised manner. We concentrate on the setting where the training data consists of a set of audio re…
Low-Resource Neural Headline Generation
Ottokar Tilk, Tanel Alumäe
Recent neural headline generation models have shown great results, but are generally trained on very large datasets. We focus our efforts on improving headline quality on smaller d…