Preserving privacy in speaker and speech characterisation

A Nautsch, A Jiménez, A Treiber, J Kolberg… - Computer Speech & …, 2019 - Elsevier
Speech recordings are a rich source of personal, sensitive data that can be used to support
a plethora of diverse applications, from health profiling to biometric recognition. It is therefore …

A report on the 2017 native language identification shared task

S Malmasi, K Evanini, A Cahill, J Tetreault… - Proceedings of the …, 2017 - aclanthology.org
Abstract Native Language Identification (NLI) is the task of automatically identifying the
native language (L1) of an individual based on their language production in a learned …

[PDF][PDF] Deep learning based mandarin accent identification for accent robust ASR.

F Weninger, Y Sun, J Park, D Willett, P Zhan - INTERSPEECH, 2019 - isca-archive.org
In this paper, we present an in-depth study on the classification of regional accents in
Mandarin speech. Experiments are carried out on Mandarin speech data systematically …

[PDF][PDF] Pathological speech detection using x-vector embeddings

C Botelho, F Teixeira, T Rolland, A Abad… - arXiv preprint arXiv …, 2020 - researchgate.net
The potential of speech as a non-invasive biomarker to assess a speaker's health has been
repeatedly supported by the results of multiple works, for both physical and psychological …

Native language identification in very short utterances using bidirectional long short-term memory network

F Adeeba, S Hussain - IEEE Access, 2019 - ieeexplore.ieee.org
Native language identification (NLI) is the task of identifying the first language of a user
based on their speech or written text in a second language. In this paper, we propose the …

Mel-weighted single frequency filtering spectrogram for dialect identification

R Kethireddy, SR Kadiri, P Alku… - IEEE Access, 2020 - ieeexplore.ieee.org
In this study, we propose Mel-weighted single frequency filtering (SFF) spectrograms for
dialect identification. The spectrum derived using SFF has high spectral resolution for …

Exploring end-to-end attention-based neural networks for native language identification

R Ubale, Y Qian, K Evanini - 2018 IEEE spoken language …, 2018 - ieeexplore.ieee.org
Automatic identification of speakers' native language (L1) based on their speech in a second
language (L2) is a challenging research problem that can aid several spoken language …

An automated classification system based on regional accent

RK Guntur, K Ramakrishnan… - Circuits, Systems, and …, 2022 - Springer
Identification of the native language from speech segment of a second language utterance,
that is manifested as a distinct pattern of articulatory or prosodic behavior, is a challenging …

Zero-time windowing cepstral coefficients for dialect classification

R Kethireddy, S Kadiri, S Kesiraju… - Odyssey: The Speaker …, 2020 - research.aalto.fi
In this paper, we propose to use novel acoustic features, namely zero-time windowing
cepstral coefficients (ZTWCC) for dialect classification. ZTWCC features are derived from …

[PDF][PDF] Improving Sub-Phone Modeling for Better Native Language Identification with Non-Native English Speech.

Y Qian, K Evanini, X Wang, D Suendermann-Oeft… - Interspeech, 2017 - convelatrade.com
Identifying a speaker's native language with his speech in a second language is useful for
many human-machine voice interface applications. In this paper, we use a sub-phone …