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20202026
most citedHow Phonotactics Affect Multilingual and Zero-shot ASR Performance

14 citations · 16 across the 10 of their papers we have counts for

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8 papers · 1 filter

eess.AS2026

Layer-Aware Early Fusion of Acoustic and Linguistic Embeddings for Cognitive Status Classification

Krystof Novotny, Laureano Moro-Velázquez, Jiri Mekyska

Speech contains both acoustic and linguistic patterns that reflect cognitive decline, and therefore models describing only one domain cannot fully capture such complexity. This stu…

eess.AS2023

Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition

Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +2

Speech super-resolution/Bandwidth Extension (BWE) can improve downstream tasks like Automatic Speaker Verification (ASV). We introduce a simple novel technique called Self-FiLM to…

eess.AS2022★ 1 cited

Time-domain speech super-resolution with GAN based modeling for telephony speaker verification

Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +2

Automatic Speaker Verification (ASV) technology has become commonplace in virtual assistants. However, its performance suffers when there is a mismatch between the train and test d…

eess.AS2022

Joint domain adaptation and speech bandwidth extension using time-domain GANs for speaker verification

Saurabh Kataria, Jesús Villalba, Laureano Moro-Velázquez +1

Speech systems developed for a particular choice of acoustic domain and sampling frequency do not translate easily to others. The usual practice is to learn domain adaptation and b…

eess.AS2021

Deep Feature CycleGANs: Speaker Identity Preserving Non-parallel Microphone-Telephone Domain Adaptation for Speaker Verification

Saurabh Kataria, Jesús Villalba, Piotr Żelasko +2

With the increase in the availability of speech from varied domains, it is imperative to use such out-of-domain data to improve existing speech systems. Domain adaptation is a prom…

eess.AS2021★ 1 cited

Unsupervised Acoustic Unit Discovery by Leveraging a Language-Independent Subword Discriminative Feature Representation

Siyuan Feng, Piotr Żelasko, Laureano Moro-Velázquez +1

This paper tackles automatically discovering phone-like acoustic units (AUD) from unlabeled speech data. Past studies usually proposed single-step approaches. We propose a two-stag…

eess.AS2020★ 14 cited

How Phonotactics Affect Multilingual and Zero-shot ASR Performance

Siyuan Feng, Piotr Żelasko, Laureano Moro-Velázquez +4

The idea of combining multiple languages' recordings to train a single automatic speech recognition (ASR) model brings the promise of the emergence of universal speech representati…

eess.AS2020

That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages

Piotr Żelasko, Laureano Moro-Velázquez, Mark Hasegawa-Johnson +2

Only a handful of the world's languages are abundant with the resources that enable practical applications of speech processing technologies. One of the methods to overcome this pr…