Low resource point process models for keyword spotting using unsupervised online learning. - Samik Sadhu; Prasanta Kumar Ghosh (EUSIPCO, 2017)

M-vectors: Sub-band Based Energy Modulation Features for Multi-stream Automatic Speech Recognition. - Samik Sadhu; Ruizhi Li; Hynek Hermansky (ICASSP, 2019)

Modulation Vectors as Robust Feature Representation for ASR in Domain Mismatched Conditions. - Samik Sadhu; Hynek Hermansky (INTERSPEECH, 2019)

Exploring Methods for the Automatic Detection of Errors in Manual Transcription. - Xiaofei Wang 007; Jinyi Yang; Ruizhi Li; Samik Sadhu; Hynek Hermansky (INTERSPEECH, 2019)

Continual Learning in Automatic Speech Recognition. - Samik Sadhu; Hynek Hermansky (INTERSPEECH, 2020)

Radically Old Way of Computing Spectra: Applications in End-to-End ASR. - Samik Sadhu; Hynek Hermansky (Interspeech, 2021)

wav2vec-C: A Self-Supervised Model for Speech Representation Learning. - Samik Sadhu; Di He 004; Che-Wei Huang; Sri Harish Mallidi; Minhua Wu; Ariya Rastrow; Andreas Stolcke; Jasha Droppo; Roland Maas (Interspeech, 2021)

Complex Frequency Domain Linear Prediction: A Tool to Compute Modulation Spectrum of Speech. - Samik Sadhu; Hynek Hermansky (INTERSPEECH, 2022)

Dealing with Unknowns in Continual Learning for End-to-end Automatic Speech Recognition. - Martin Sustek; Samik Sadhu; Hynek Hermansky (INTERSPEECH, 2022)

Blind Signal Dereverberation for Machine Speech Recognition. - Samik Sadhu; Hynek Hermansky (CoRR, 2022)

Importance of Different Temporal Modulations of Speech: a Tale of two Perspectives. - Samik Sadhu; Hynek Hermansky (ICASSP, 2023)

Stabilized training of joint energy-based models and their practical applications. - Martin Sustek; Samik Sadhu; Lukás Burget; Hynek Hermansky; Jesús Villalba 001; Laureano Moro-Velázquez; Najim Dehak (CoRR, 2023)

Self-supervised Learning with Speech Modulation Dropout. - Samik Sadhu; Hynek Hermansky (CoRR, 2023)