activity
20162022
most citedLeveraging native language information for improved accented speech recognition

28 citations · 112 across the 23 of their papers we have counts for

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7 papers · 1 filter

cs.SD20211 cited

Scenario Aware Speech Recognition: Advancements for Apollo Fearless Steps & CHiME-4 Corpora

Szu-Jui Chen, Wei Xia, John H. L. Hansen

In this study, we propose to investigate triplet loss for the purpose of an alternative feature representation for ASR. We consider a general non-semantic speech representation, wh…

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…

cs.SD2019

Toeplitz Inverse Covariance based Robust Speaker Clustering for Naturalistic Audio Streams

Harishchandra Dubey, Abhijeet Sangwan, John Hansen

Speaker diarization determines who spoke and when? in an audio stream. In this study, we propose a model-based approach for robust speaker clustering using i-vectors. The ivectors…

cs.SD2019

Convolutional Neural Network-based Speech Enhancement for Cochlear Implant Recipients

Nursadul Mamun, Soheil Khorram, John H. L. Hansen

Attempts to develop speech enhancement algorithms with improved speech intelligibility for cochlear implant (CI) users have met with limited success. To improve speech enhancement…

cs.SD2018

Robust Speaker Clustering using Mixtures of von Mises-Fisher Distributions for Naturalistic Audio Streams

Harishchandra Dubey, Abhijeet Sangwan, John H. L. Hansen

Speaker Diarization (i.e. determining who spoke and when?) for multi-speaker naturalistic interactions such as Peer-Led Team Learning (PLTL) sessions is a challenging task. In this…

cs.SD2018

Robust Feature Clustering for Unsupervised Speech Activity Detection

Harishchandra Dubey, Abhijeet Sangwan, John H. L. Hansen

In certain applications such as zero-resource speech processing or very-low resource speech-language systems, it might not be feasible to collect speech activity detection (SAD) an…