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20212026
most citedInvestigation of Whisper ASR Hallucinations Induced by Non-Speech Audio

7 citations · 12 across the 6 of their papers we have counts for

collaborators

7 papers

cs.SD2026

Toward Complete Speaker Anonymization: a Streaming Cascaded System for Voice Privacy and PII Removal

Stanisław Kacprzak, Thomas Thebaud, Najim Dehak

We present a cascade streaming voice privacy system, consisting of ASR, NLP, and TTS modules. By leveraging recent improvements in all three aspects of speech and language processi…

eess.AS2026

The Hidden Cost of Digits: Number Normalization and WER in ASR Systems

Stanisław Kacprzak, Mieszko Fraś

Modern automatic speech recognition (ASR) systems trained on extremely large datasets can produce transcripts with numbers written in Arabic numerals. This creates a need for fair…

cs.SD2025★ 7 cited

Investigation of Whisper ASR Hallucinations Induced by Non-Speech Audio

Mateusz Barański, Jan Jasiński, Julitta Bartolewska +3

Hallucinations of deep neural models are amongst key challenges in automatic speech recognition (ASR). In this paper, we investigate hallucinations of the Whisper ASR model induced…

cs.SD2024★ 2 cited

HeightCeleb - an enrichment of VoxCeleb dataset with speaker height information

Stanisław Kacprzak, Konrad Kowalczyk

Prediction of speaker's height is of interest for voice forensics, surveillance, and automatic speaker profiling. Until now, TIMIT has been the most popular dataset for training an…

eess.AS2023

Refining DNN-based Mask Estimation using CGMM-based EM Algorithm for Multi-channel Noise Reduction

Julitta Bartolewska, Stanisław Kacprzak, Konrad Kowalczyk

In this paper, we present a method that allows to further improve speech enhancement obtained with recently introduced Deep Neural Network (DNN) models. We propose a multi-channel…

eess.AS2023★ 2 cited

Causal Signal-Based DCCRN with Overlapped-Frame Prediction for Online Speech Enhancement

Julitta Bartolewska, Stanisław Kacprzak, Konrad Kowalczyk

The aim of speech enhancement is to improve speech signal quality and intelligibility from a noisy microphone signal. In many applications, it is crucial to enable processing with…

cs.SD2021★ 1 cited

Adversarial Domain Adaptation with Paired Examples for Acoustic Scene Classification on Different Recording Devices

Stanisław Kacprzak, Konrad Kowalczyk

In classification tasks, the classification accuracy diminishes when the data is gathered in different domains. To address this problem, in this paper, we investigate several adver…