| Dereverberation of autoregressive envelopes for far-field speech recognition | 0 | 0.34 | 2022 |
| End-To-End Speech Recognition with Joint Dereverberation of Sub-Band Autoregressive Envelopes | 0 | 0.34 | 2022 |
| Self-Supervised Metric Learning With Graph Clustering For Speaker Diarization | 0 | 0.34 | 2021 |
| SRIB-LEAP Submission to Far-Field Multi-Channel Speech Enhancement Challenge for Video Conferencing. | 0 | 0.34 | 2021 |
| DiCOVA Challenge - Dataset, Task, and Baseline System for COVID-19 Diagnosis Using Acoustics. | 0 | 0.34 | 2021 |
| DEEP MULTIWAY CANONICAL CORRELATION ANALYSIS FOR MULTI-SUBJECT EEG NORMALIZATION | 0 | 0.34 | 2021 |
| A Multi-Head Relevance Weighting Framework for Learning Raw Waveform Audio Representations | 0 | 0.34 | 2021 |
| End-to-end lyrics Recognition with Voice to Singing Style Transfer | 0 | 0.34 | 2021 |
| REPRESENTATION LEARNING FOR SPEECH RECOGNITION USING FEEDBACK BASED RELEVANCE WEIGHTING | 0 | 0.34 | 2021 |
| The Third DIHARD Diarization Challenge. | 0 | 0.34 | 2021 |
| LEAP Submission for the Third DIHARD Diarization Challenge. | 0 | 0.34 | 2021 |
| NISP: A Multi-lingual Multi-accent Dataset for Speaker Profiling | 0 | 0.34 | 2021 |
| Context Dependent RNNLM for Automatic Transcription of Conversations | 0 | 0.34 | 2020 |
| Robust Raw Waveform Speech Recognition Using Relevance Weighted Representations | 0 | 0.34 | 2020 |
| Automatic speaker profiling from short duration speech data. | 1 | 0.36 | 2020 |
| Improving Voice Separation by Incorporating End-To-End Speech Recognition | 1 | 0.38 | 2020 |
| Audiovisual Correspondence Learning in Humans and Machines. | 0 | 0.34 | 2020 |
| IITG- Indigo Submissions for NIST 2018 Speaker Recognition Evaluation and Post-Challenge Improvements | 0 | 0.34 | 2020 |
| NPLDA - A Deep Neural PLDA Model for Speaker Verification. | 2 | 0.37 | 2020 |
| Deep Self-Supervised Hierarchical Clustering for Speaker Diarization | 0 | 0.34 | 2020 |
| LEAP System for SRE 2019 CTS Challenge - Improvements and Error Analysis. | 0 | 0.34 | 2020 |
| Coswara -- A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis | 6 | 0.62 | 2020 |
| Deep Learning Based Dereverberation of Temporal Envelopesfor Robust Speech Recognition | 2 | 0.40 | 2020 |
| Supervised I-vector Modeling for Language and Accent Recognition | 0 | 0.34 | 2020 |
| Deep Canonical Correlation Analysis For Decoding The Auditory Brain | 1 | 0.36 | 2020 |
| Neural PLDA Modeling for End-to-End Speaker Verification | 1 | 0.35 | 2020 |
| Analyzing Human Reaction Time For Talker Change Detection | 0 | 0.34 | 2019 |
| Level-Wise Subject Adaptation To Improve Classification Of Motor And Mental Eeg Tasks | 0 | 0.34 | 2019 |
| Speaker and Language Aware Training for End-to-End ASR | 0 | 0.34 | 2019 |
| Unsupervised Raw Waveform Representation Learning for ASR | 0 | 0.34 | 2019 |
| Modulation Filter Learning Using Deep Variational Networks for Robust Speech Recognition | 2 | 0.35 | 2019 |
| A Deep Neural Network Based End To End Model For Joint Height And Age Estimation From Short Duration Speech | 0 | 0.34 | 2019 |
| Deep Variational Filter Learning Models For Speech Recognition | 0 | 0.34 | 2019 |
| LEAP diarization system for the second DIHARD challenge | 0 | 0.34 | 2019 |
| End-To-End Language Recognition Using Attention Based Hierarchical Gated Recurrent Unit Models | 0 | 0.34 | 2019 |
| A study of X-vector based speaker recognition on short utterances | 0 | 0.34 | 2019 |
| Active Learning Methods for Low Resource End-to-End Speech Recognition | 1 | 0.37 | 2019 |
| Attention Based Hybrid i-Vector BLSTM Model for Language Recognition | 2 | 0.38 | 2019 |
| The Second DIHARD Diarization Challenge: Dataset, task, and baselines. | 2 | 0.36 | 2019 |
| The Second DIHARD Diarization Challenge - Dataset, Task, and Baselines. | 1 | 0.36 | 2019 |
| The Leap Speaker Recognition System For Nist Sre 2018 Challenge | 0 | 0.34 | 2019 |
| Second Language Transfer Learning In Humans And Machines Using Image Supervision | 0 | 0.34 | 2019 |
| The LEAP Language Recognition System for LRE 2017 Challenge - Improvements and Error Analysis. | 0 | 0.34 | 2018 |
| Leveraging Native Language Speech For Accent Identification Using Deep Siamese Networks | 0 | 0.34 | 2017 |
| Multivariate Autoregressive Spectrogram Modeling for Noisy Speech Recognition. | 0 | 0.34 | 2017 |
| Speech Representation Learning Using Unsupervised Data-Driven Modulation Filtering For Robust Asr | 0 | 0.34 | 2017 |
| Iitg-Indigo System For Nist 2016 Sre Challenge | 2 | 0.41 | 2017 |
| Increasing the robustness of CNN acoustic models using autoregressive moving average spectrogram features and channel dropout. | 0 | 0.34 | 2017 |
| Unsupervised Hmm Posteriograms For Language Independent Acoustic Modeling In Zero Resource Conditions | 0 | 0.34 | 2017 |
| Deep Learning Methods For Unsupervised Acoustic Modeling - Leap Submission To Zerospeech Challenge 2017 | 0 | 0.34 | 2017 |
