On-the-fly data loader and utterance-level aggregation for speaker and language recognition

W Cai, J Chen, J Zhang, M Li - IEEE/ACM Transactions on …, 2020 - ieeexplore.ieee.org
In this article, our recent efforts on directly modeling utterance-level aggregation for speaker
and language recognition is summarized. First, an on-the-fly data loader for efficient network …

An overview of Indian spoken language recognition from machine learning perspective

S Dey, M Sahidullah, G Saha - ACM Transactions on Asian and Low …, 2022 - dl.acm.org
Automatic spoken language identification (LID) is a very important research field in the era of
multilingual voice-command-based human-computer interaction. A front-end LID module …

Short utterance based speech language identification in intelligent vehicles with time-scale modifications and deep bottleneck features

Z Ma, H Yu, W Chen, J Guo - IEEE transactions on vehicular …, 2018 - ieeexplore.ieee.org
Conversations in the intelligent vehicles are usually short utterance. As the durations of the
short utterances are small (eg, less than 3 s), it is difficult to learn sufficient information to …

AP20-OLR challenge: Three tasks and their baselines

Z Li, M Zhao, Q Hong, L Li, Z Tang… - 2020 Asia-Pacific …, 2020 - ieeexplore.ieee.org
This paper introduces the fifth oriental language recognition (OLR) challenge AP20-OLR,
which intends to improve the performance of language recognition systems, along with …

[PDF][PDF] An End-to-End Dialect Identification System with Transfer Learning from a Multilingual Automatic Speech Recognition Model.

D Wang, S Ye, X Hu, S Li, X Xu - Interspeech, 2021 - researchgate.net
In this paper, we propose an end-to-end (E2E) dialect identification system trained using
transfer learning from a multilingual automatic speech recognition (ASR) model. This is also …

AP19-OLR challenge: Three tasks and their baselines

Z Tang, D Wang, L Song - 2019 Asia-Pacific Signal and …, 2019 - ieeexplore.ieee.org
This paper introduces the fourth oriental language recognition (OLR) challenge AP19-OLR,
including the data profile, the tasks and the evaluation principles. The OLR challenge has …

PHO-LID: A unified model incorporating acoustic-phonetic and phonotactic information for language identification

H Liu, LPG Perera, AWH Khong, SJ Styles… - arxiv preprint arxiv …, 2022 - arxiv.org
We propose a novel model to hierarchically incorporate phoneme and phonotactic
information for language identification (LID) without requiring phoneme annotations for …

Olr 2021 challenge: Datasets, rules and baselines

B Wang, W Hu, J Li, Y Zhi, Z Li, Q Hong… - 2021 Asia-Pacific …, 2021 - ieeexplore.ieee.org
This paper introduces the sixth Oriental Language Recognition (OLR) 2021 Challenge,
which intends to improve the performance of language recognition systems and speech …

Deep joint learning for language recognition

L Li, Z Li, Y Liu, Q Hong - Neural Networks, 2021 - Elsevier
Deep learning methods for language recognition have achieved promising performance.
However, most of the studies focus on frameworks for single types of acoustic features and …

Curriculum learning based approach for noise robust language identification using DNN with attention

RK Vuddagiri, HK Vydana, AK Vuppala - Expert Systems with Applications, 2018 - Elsevier
Automatic language identification (LID) in practical environments is gaining a lot of scientific
attention due to rapid developments in multilingual speech processing applications. When …