Multi-layer perceptron based speech activity detection for speaker verification. - Sriram Ganapathy; Padmanabhan Rajan; Hynek Hermansky (WASPAA, 2011)

The UMD-JHU 2011 speaker recognition system. - Daniel Garcia-Romero; Xinhui Zhou; Dmitry N. Zotkin; Balaji Vasan Srinivasan; Yuancheng Luo; Sriram Ganapathy; Samuel Thomas 001; Sridhar Krishna Nemala; Garimella S. V. S. Sivaram; Majid Mirbagheri; Sri Harish Reddy Mallidi; Thomas Janu; et al. (ICASSP, 2012)

Group Delay Function from All-Pole Models for Musical Instrument Recognition. - Aleksandr Diment; Padmanabhan Rajan; Toni Heittola; Tuomas Virtanen (CMMR, 2013)

A practical, self-adaptive voice activity detector for speaker verification with noisy telephone and microphone data. - Tomi Kinnunen; Padmanabhan Rajan (ICASSP, 2013)

Comparison of spectrum estimators in speaker verification: mismatch conditions induced by vocal effort. - Cemal Hanilçi; Tomi Kinnunen; Padmanabhan Rajan; Jouni Pohjalainen; Paavo Alku; Figen Ertas (INTERSPEECH, 2013)

Minimax i-vector extractor for short duration speaker verification. - Ville Hautamäki; You-Chi Cheng; Padmanabhan Rajan; Chin-Hui Lee 001 (INTERSPEECH, 2013)

Merging human and automatic system decisions to improve speaker recognition performance. - Rosa González Hautamäki; Ville Hautamäki; Padmanabhan Rajan; Tomi Kinnunen (INTERSPEECH, 2013)

Effect of multicondition training on i-vector PLDA configurations for speaker recognition. - Padmanabhan Rajan; Tomi Kinnunen; Ville Hautamäki (INTERSPEECH, 2013)

Using group delay functions from all-pole models for speaker recognition. - Padmanabhan Rajan; Tomi Kinnunen; Cemal Hanilçi; Jouni Pohjalainen; Paavo Alku (INTERSPEECH, 2013)

I4u submission to NIST SRE 2012: a large-scale collaborative effort for noise-robust speaker verification. - Rahim Saeidi; Kong-Aik Lee; Tomi Kinnunen; Tawfik Hasan; Benoit G. B. Fauve; Pierre-Michel Bousquet; Elie Khoury 001; Pablo Luis Sordo Martinez; Jia Min Karen Kua; Changhuai You; Hanwu Sun; Anthony Larcher; et al. (INTERSPEECH, 2013)

From single to multiple enrollment i-vectors: Practical PLDA scoring variants for speaker verification. - Padmanabhan Rajan; Anton Afanasyev; Ville Hautamäki; Tomi Kinnunen (Digit. Signal Process., 2014)

Bird Call Identification Using Dynamic Kernel Based Support Vector Machines and Deep Neural Networks. - Deep Chakraborty; Paawan Mukker; Padmanabhan Rajan; Aroor Dinesh Dileep (ICMLA, 2016)

Model-based unsupervised segmentation of birdcalls from field recordings. - Anshul Thakur; Padmanabhan Rajan (ICSPCS, 2016)

Archetypal analysis based sparse convex sequence kernel for bird activity detection. - Vinayak Abrol; Pulkit Sharma; Anshul Thakur; Padmanabhan Rajan; Aroor Dinesh Dileep; Anil Kumar Sao (EUSIPCO, 2017)

Rapid bird activity detection using probabilistic sequence kernels. - Anshul Thakur; R. Jyothi; Padmanabhan Rajan; Aroor Dinesh Dileep (EUSIPCO, 2017)

Rényi entropy based mutual information for semi-supervised bird vocalization segmentation. - Anshul Thakur; Vinayak Abrol; Pulkit Sharma; Padmanabhan Rajan (MLSP, 2017)

Unsupervised birdcall activity detection using source and system features. - Anshul Thakur; Padmanabhan Rajan (NCC, 2017)

A Layer-wise Score Level Ensemble Framework for Acoustic Scene Classification. - Arshdeep Singh; Anshul Thakur; Padmanabhan Rajan; Arnav Bhavsar (EUSIPCO, 2018)

Compressed Convex Spectral Embedding for Bird Species Classification. - Anshul Thakur; Vinayak Abrol; Pulkit Sharma; Padmanabhan Rajan (ICASSP, 2018)

Feature learning for bird-call segmentation using phase based features. - Rhythm Bhatia; Harshita Seth; Padmanabhan Rajan (ICIIS, 2018)

Feature Learning for Bird Call Clustering. - Harshita Seth; Rhythm Bhatia; Padmanabhan Rajan (ICIIS, 2018)

A Deep Autoencoder Approach To Bird Call Enhancement. - Ragini Sinha; Padmanabhan Rajan (ICIIS, 2018)

All-Conv Net for Bird Activity Detection: Significance of Learned Pooling. - Arjun Pankajakshan; Anshul Thakur; Daksh Thapar; Padmanabhan Rajan; Aditya Nigam (INTERSPEECH, 2018)

Deep Convex Representations: Feature Representations for Bioacoustics Classification. - Anshul Thakur; Vinayak Abrol; Pulkit Sharma; Padmanabhan Rajan (INTERSPEECH, 2018)

APE: Archetypal-Prototypal Embeddings for Audio Classification. - Arshdeep Singh; Anshul Thakur; Padmanabhan Rajan (MLSP, 2018)

Convex likelihood alignments for bioacoustic Classification. - Anshul Thakur; Arshdeep Singh; Padmanabhan Rajan (MLSP, 2018)

Deep Multi-view Features from Raw Audio for Acoustic Scene Classification. - Arshdeep Singh; Padmanabhan Rajan; Arnav Bhavsar (DCASE, 2019)

Deep Hidden Analysis: A Statistical Framework to Prune Feature Maps. - Arshdeep Singh; Padmanabhan Rajan; Arnav Bhavsar (ICASSP, 2019)

CONV-codes: Audio Hashing for Bird Species Classification. - Anshul Thakur; Pulkit Sharma; Vinayak Abrol; Padmanabhan Rajan (ICASSP, 2019)

Single versus Multi-Source Discrimination in Birdcalls using Zero-Frequency Filtering. - Ragini Sinha; Vivek Vadluri; Ashish Arya; Padmanabhan Rajan (NCC, 2019)

Directional Embedding Based Semi-supervised Framework For Bird Vocalization Segmentation. - Anshul Thakur; Padmanabhan Rajan (CoRR, 2019)

Multiscale CNN based Deep Metric Learning for Bioacoustic Classification: Overcoming Training Data Scarcity Using Dynamic Triplet Loss. - Anshul Thakur; Daksh Thapar; Padmanabhan Rajan; Aditya Nigam (CoRR, 2019)

Deep Archetypal Analysis Based Intermediate Matching Kernel for Bioacoustic Classification. - Anshul Thakur; Padmanabhan Rajan (IEEE J. Sel. Top. Signal Process., 2019)

Learning to Separate: Soundscape Classification using Foreground and Background. - Dhanunjaya Varma Devalraju; Padmanabhan Rajan; Aroor Dinesh Dileep (EUSIPCO, 2020)

Attention-Driven Projections for Soundscape Classification. - Dhanunjaya Varma Devalraju; H. Muralikrishna; Padmanabhan Rajan; Dileep Aroor Dinesh (INTERSPEECH, 2020)

SVD-based redundancy removal in 1-D CNNs for acoustic scene classification. - Arshdeep Singh; Padmanabhan Rajan; Arnav Bhavsar (Pattern Recognit. Lett., 2020)

Spoken Language Identification in Unseen Target Domain Using Within-Sample Similarity Loss. - Muralikrishna H; Shantanu Kapoor; Dileep Aroor Dinesh; Padmanabhan Rajan (ICASSP, 2021)

Noise-Robust Spoken Language Identification Using Language Relevance Factor Based Embedding. - Muralikrishna H; Shikha Gupta; Dileep Aroor Dinesh; Padmanabhan Rajan (SLT, 2021)

Health Monitoring of Industrial machines using Scene-Aware Threshold Selection. - Arshdeep Singh; Raju Arvind; Padmanabhan Rajan (CoRR, 2021)

Location-invariant representations for acoustic scene classification. - Akansha Tyagi; Padmanabhan Rajan (EUSIPCO, 2022)

Multiview Embeddings for Soundscape Classification. - Dhanunjaya Varma Devalraju; Padmanabhan Rajan (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Sparse Representation Frameworks for Acoustic Scene Classification. - Akansha Tyagi; Padmanabhan Rajan (SPECOM (1), 2023)

Neural Networks for Interference Reduction in Multi-Track Recordings. - Rajesh R; Padmanabhan Rajan (WASPAA, 2023)

Is That Me? Using Speaker Identity to Detect Fake Speech. - Shilpa Chandra; Padmanabhan Rajan (MLSP, 2024)