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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…
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…
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…
Jointly Aligning and Predicting Continuous Emotion Annotations
Soheil Khorram, Melvin G McInnis, Emily Mower Provost
Time-continuous dimensional descriptions of emotions (e.g., arousal, valence) allow researchers to characterize short-time changes and to capture long-term trends in emotion expres…
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…
Trainable Time Warping: Aligning Time-Series in the Continuous-Time Domain
Soheil Khorram, Melvin G McInnis, Emily Mower Provost
DTW calculates the similarity or alignment between two signals, subject to temporal warping. However, its computational complexity grows exponentially with the number of time-serie…