419 citations · 427 across the 12 of their papers we have counts for
16 papers
Audio Source Separation in Reverberant Environments using -divergence based Nonnegative Factorization
Mahmoud Fakhry, Piergiorgio Svaizer, Maurizio Omologo
In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral variances and by associated s…
Leveraging Redundancy in Multiple Audio Signals for Far-Field Speech Recognition
Feng-Ju Chang, Anastasios Alexandridis, Rupak Vignesh Swaminathan +6
To achieve robust far-field automatic speech recognition (ASR), existing techniques typically employ an acoustic front end (AFE) cascaded with a neural transducer (NT) ASR model. T…
A neural prosody encoder for end-ro-end dialogue act classification
Kai Wei, Dillon Knox, Martin Radfar +6
Dialogue act classification (DAC) is a critical task for spoken language understanding in dialogue systems. Prosodic features such as energy and pitch have been shown to be useful…
Context-Aware Transformer Transducer for Speech Recognition
Feng-Ju Chang, Jing Liu, Martin Radfar +4
End-to-end (E2E) automatic speech recognition (ASR) systems often have difficulty recognizing uncommon words, that appear infrequently in the training data. One promising method, t…
Multi-Channel Transformer Transducer for Speech Recognition
Feng-Ju Chang, Martin Radfar, Athanasios Mouchtaris +1
Multi-channel inputs offer several advantages over single-channel, to improve the robustness of on-device speech recognition systems. Recent work on multi-channel transformer, has…
Sample Drop Detection for Distant-speech Recognition with Asynchronous Devices Distributed in Space
Tina Raissi, Santiago Pascual, Maurizio Omologo
In many applications of multi-microphone multi-device processing, the synchronization among different input channels can be affected by the lack of a common clock and isolated drop…
DiPCo -- Dinner Party Corpus
Maarten Van Segbroeck, Ahmed Zaid, Ksenia Kutsenko +7
We present a speech data corpus that simulates a "dinner party" scenario taking place in an everyday home environment. The corpus was created by recording multiple groups of four A…
LOCATA challenge: speaker localization with a planar array
Xinyuan Qian, Andrea Cavallaro, Alessio Brutti +1
This document describes our submission to the 2018 LOCalization And TrAcking (LOCATA) challenge (Tasks 1, 3, 5). We estimate the 3D position of a speaker using the Global Coherence…
Automatic context window composition for distant speech recognition
Mirco Ravanelli, Maurizio Omologo
Distant speech recognition is being revolutionized by deep learning, that has contributed to significantly outperform previous HMM-GMM systems. A key aspect behind the rapid rise a…
Light Gated Recurrent Units for Speech Recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
A field that has directly benefited from the recent advances in deep learning is Automatic Speech Recognition (ASR). Despite the great achievements of the past decades, however, a…
Realistic multi-microphone data simulation for distant speech recognition
Mirco Ravanelli, Piergiorgio Svaizer, Maurizio Omologo
The availability of realistic simulated corpora is of key importance for the future progress of distant speech recognition technology. The reliability, flexibility and low computat…
Contaminated speech training methods for robust DNN-HMM distant speech recognition
Mirco Ravanelli, Maurizio Omologo
Despite the significant progress made in the last years, state-of-the-art speech recognition technologies provide a satisfactory performance only in the close-talking condition. Ro…
The DIRHA-English corpus and related tasks for distant-speech recognition in domestic environments
Mirco Ravanelli, Maurizio Omologo
This paper introduces the contents and the possible usage of the DIRHA-ENGLISH multi-microphone corpus, recently realized under the EC DIRHA project. The reference scenario is a do…
Improving speech recognition by revising gated recurrent units
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Speech recognition is largely taking advantage of deep learning, showing that substantial benefits can be obtained by modern Recurrent Neural Networks (RNNs). The most popular RNNs…
Batch-normalized joint training for DNN-based distant speech recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Improving distant speech recognition is a crucial step towards flexible human-machine interfaces. Current technology, however, still exhibits a lack of robustness, especially when…
A network of deep neural networks for distant speech recognition
Mirco Ravanelli, Philemon Brakel, Maurizio Omologo +1
Despite the remarkable progress recently made in distant speech recognition, state-of-the-art technology still suffers from a lack of robustness, especially when adverse acoustic c…