activity
20162023
most citedLeveraging native language information for improved accented speech recognition

28 citations · 113 across the 24 of their papers we have counts for

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Showing 2019Show all

10 papers · 1 filter

cs.LG20194 cited

A Unified Framework for Speech Separation

Fahimeh Bahmaninezhad, Shi-Xiong Zhang, Yong Xu +3

Speech separation refers to extracting each individual speech source in a given mixed signal. Recent advancements in speech separation and ongoing research in this area, have made…

eess.AS2019

Analyzing Large Receptive Field Convolutional Networks for Distant Speech Recognition

Salar Jafarlou, Soheil Khorram, Vinay Kothapally +1

Despite significant efforts over the last few years to build a robust automatic speech recognition (ASR) system for different acoustic settings, the performance of the current stat…

eess.AS20191 cited

Domain Expansion in DNN-based Acoustic Models for Robust Speech Recognition

Shahram Ghorbani, Soheil Khorram, John H. L. Hansen

Training acoustic models with sequentially incoming data -- while both leveraging new data and avoiding the forgetting effect-- is an essential obstacle to achieving human intellig…

eess.AS2019

Cross-lingual Text-independent Speaker Verification using Unsupervised Adversarial Discriminative Domain Adaptation

Wei Xia, Jing Huang, John H. L. Hansen

Speaker verification systems often degrade significantly when there is a language mismatch between training and testing data. Being able to improve cross-lingual speaker verificati…

eess.AS2019

Probabilistic Permutation Invariant Training for Speech Separation

Midia Yousefi, Soheil Khorram, John H. L. Hansen

Single-microphone, speaker-independent speech separation is normally performed through two steps: (i) separating the specific speech sources, and (ii) determining the best output-l…

cs.SD2019

Quantifying Cochlear Implant Users' Ability for Speaker Identification using CI Auditory Stimuli

Nursadul Mamun, Ria Ghosh, John H. L. Hansen

Speaker recognition is a biometric modality that uses underlying speech information to determine the identity of the speaker. Speaker Identification (SID) under noisy conditions is…