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Odyssey 2016: Bilbao, Spain
- Luis Javier Rodríguez-Fuentes, Eduardo Lleida:
Odyssey 2016: The Speaker and Language Recognition Workshop, Bilbao, Spain, June 21-24, 2016. ISCA 2016
Keynote: Haizhou Li
- Haizhou Li:
Voice conversion and spoofing countermeasures for speaker verification.
Text-Dependent Speaker Verification
- Qing He, Gregory W. Wornell, Wei Ma:
A Low-Power Text-Dependent Speaker Verification System with Narrow-Band Feature Pre-Selection and Weighted Dynamic Time Warping. 1-8 - Gautam Bhattacharya, Patrick Kenny, Jahangir Alam, Themos Stafylakis:
Deep Neural Network based Text-Dependent Speaker Verification : Preliminary Results. 9-15 - Patrick Kenny, Themos Stafylakis, Jahangir Alam, Vishwa Gupta, Marcel Kockmann:
Uncertainty Modeling Without Subspace Methods For Text-Dependent Speaker Recognition. 16-23 - Hossein Zeinali, Lukás Burget
, Hossein Sameti, Ondrej Glembek, Oldrich Plchot:
Deep Neural Networks and Hidden Markov Models in i-vector-based Text-Dependent Speaker Verification. 24-30
Speaker Recognition: i-vector approaches
- Wei-Wei Lin
Fast Scoring for PLDA with Uncertainty Propagation. 31-38 - Sandro Cumani, Pietro Laface:
I-vector transformation and scaling for PLDA based speaker recognition. 39-46 - Longting Xu, Kong-Aik Lee, Haizhou Li
Rapid Computation of I-vector. 47-52 - Pierre-Michel Bousquet, Jean-François Bonastre:
Constrained discriminative speaker verification specific to normalized i-vectors. 53-59 - Waad Ben Kheder, Driss Matrouf, Moez Ajili, Jean-François Bonastre:
Iterative Bayesian and MMSE-based noise compensation techniques for speaker recognition in the i-vector space. 60-67
Language Recognition
- Abhinav Misra, Qian Zhang, Finnian Kelly, John H. L. Hansen:
Between-Class Covariance Correction For Linear Discriminant Analysis in Language Recognition. 68-73 - Amir Hossein Poorjam, Rahim Saeidi, Tomi Kinnunen, Ville Hautamäki
Incorporating uncertainty as a Quality Measure in I-Vector Based Language Recognition. 74-80 - Aleksandr Sizov, Kong-Aik Lee, Tomi Kinnunen:
Discriminating Languages in a Probabilistic Latent Subspace. 81-88 - Yao Tian, Liang He, Yi Liu, Jia Liu:
Investigation of Senone-based Long-Short Term Memory RNNs for Spoken Language Recognition. 89-93 - Georgina Brown:
Automatic Accent Recognition Systems and the Effects of Data on Performance. 94-100 - David A. van Leeuwen, Rosemary Orr:
The "Sprekend Nederland" project and its application to accent location. 101-108 - Trung Ngo Trong, Ville Hautamäki
Deep Language: a comprehensive deep learning approach to end-to-end language recognition. 109-116 - Christian Salamea
On the use of phone-gram units in recurrent neural networks for language identification. 117-123 - Gregory Gelly, Jean-Luc Gauvain, Lori Lamel, Antoine Laurent, Viet Bac Le, Abdel Messaoudi:
Language Recognition for Dialects and Closely Related Languages. 124-131 - Maryam Najafian, Saeid Safavi, Phil Weber
Identification of British English regional accents using fusion of i-vector and multi-accent phonotactic systems. 132-139 - Yan Song, Ruilian Cui, Ian McLoughlin
Improvements on Deep Bottleneck Network based I-Vector Representation for Spoken Language Identification. 140-145
Special Session 1: Speaker Recognition in Multimedia Content
- Mateusz Budnik, Ali Khodabakhsh
Deep complementary features for speaker identification in TV broadcast data. 146-151 - Gaël Le Lan, Sylvain Meignier, Delphine Charlet, Anthony Larcher:
First investigations on self trained speaker diarization. 152-157 - Brecht Desplanques, Kris Demuynck, Jean-Pierre Martens:
Soft VAD in Factor Analysis Based Speaker Segmentation of Broadcast News. 158-165
Keynote: Shrikanth Narayanan
- Shrikanth S. Narayanan:
Understanding individual-level speech variability: From novel speech production data to robust speaker recognition.
Speaker and Language Recognition Systems
- Oldrich Plchot, Pavel Matejka, Ondrej Glembek, Radek Fér, Ondrej Novotný, Jan Pesán
BAT System Description for NIST LRE 2015. 166-173 - Seyed Omid Sadjadi, Sriram Ganapathy, Jason W. Pelecanos:
The IBM 2016 Speaker Recognition System. 174-180 - Raymond W. M. Ng, Mauro Nicolao
The Sheffield language recognition system in NIST LRE 2015. 181-187 - Mitchell McLaren, Diego Castán, Luciana Ferrer:
Analyzing the Effect of Channel Mismatch on the SRI Language Recognition Evaluation 2015 System. 188-195 - Pedro A. Torres-Carrasquillo, Najim Dehak
The MITLL NIST LRE 2015 Language Recognition System. 196-203
Speaker and Language Recognition: deep learning approaches
- Alan McCree, Gregory Sell, Daniel Garcia-Romero:
Augmented Data Training of Joint Acoustic/Phonotactic DNN i-vectors for NIST LRE15. 204-209 - Ma Jin, Yan Song, Ian McLoughlin
LID-senone Extraction via Deep Neural Networks for End-to-End Language Identification. 210-216 - Timur Pekhovsky, Sergey Novoselov, Aleksei Sholohov, Oleg Kudashev:
On autoencoders in the i-vector space for speaker recognition. 217-224 - Fred Richardson, Brian E. Nemsick, Douglas A. Reynolds:
Channel Compensation for Speaker Recognition using MAP Adapted PLDA and Denoising DNNs. 225-230 - Rubén Zazo, Alicia Lozano-Diez, Joaquin Gonzalez-Rodriguez:
Evaluation of an LSTM-RNN System in Different NIST Language Recognition Frameworks. 231-236
Speaker Recognition I
- Javier Franco-Pedroso, Joaquin Gonzalez-Rodriguez:
Feature-based likelihood ratios for speaker recognition from linguistically-constrained formant-based i-vectors. 237-244 - Kuruvachan K. George, Santhosh Kumar C, K. I. Ramachandran, Ashish Panda:
Improving Robustness of Speaker Verification Against Mimicked Speech. 245-251 - Alessio Brutti, Alberto Abad:
Multi-channel i-vector combination for robust speaker verification in multi-room domestic environments. 252-258 - Sayaka Shiota, Fernando Villavicencio, Junichi Yamagishi, Nobutaka Ono
Voice Liveness Detection for Speaker Verification based on a Tandem Single/Double-channel Pop Noise Detector. 259-263 - Abbas Khosravani, Mohammad Mehdi Homayounpour, Dijana Petrovska-Delacrétaz, Gérard Chollet:
A PLDA Approach for Language and Text Independent Speaker Recognition. 264-269 - Md. Jahangir Alam, Patrick Kenny, Vishwa Gupta, Themos Stafylakis:
Spoofing Detection on the ASVspoof2015 Challenge Corpus Employing Deep Neural Networks. 270-276 - Rosa González Hautamäki, Md. Sahidullah, Tomi Kinnunen, Ville Hautamäki
Age-Related Voice Disguise and its Impact on Speaker Verification Accuracy. 277-282 - Massimiliano Todisco
A New Feature for Automatic Speaker Verification Anti-Spoofing: Constant Q Cepstral Coefficients. 283-290 - Marco Paulini, Christian Rathgeb, Andreas Nautsch
Multi-Bit Allocation: Preparing Voice Biometrics for Template Protection. 291-296
Special Session 2: NIST 2015 Language Recognition i-Vector Machine Learning Challenge
- Audrey Tong, Craig S. Greenberg, Alvin F. Martin, Désiré Bansé, John M. Howard, Hui Zhao, George R. Doddington, Daniel Garcia-Romero, Alan McCree, Douglas A. Reynolds, Elliot Singer, Jaime Hernandez-Cordero
Summary of the 2015 NIST Language Recognition i-Vector Machine Learning Challenge. 297-302 - Hamid Behravan, Tomi Kinnunen, Ville Hautamäki
Out-of-Set i-Vector Selection for Open-set Language Identification. 303-310 - Hanwu Sun, Trung Hieu Nguyen, Guangsen Wang, Kong-Aik Lee, Bin Ma, Haizhou Li
I2R Submission to the 2015 NIST Language Recognition I-vector Challenge. 311-318 - Ehud Ben-Reuven, Jacob Goldberger:
A Semisupervised Approach for Language Identification based on Ladder Networks. 319-325
Keynote: Najim Dehak
- Najim Dehak:
I-Vector Representation Based on GMM and DNN for Audio Classification.
Speaker Recognition II
- Phil Rose, Bruce Xiao Wang
Cantonese forensic voice comparison with higher-level features: likelihood ratio-based validation using F-pattern and tonal F0 trajectories over a disyllabic hexaphone. 326-333 - Elie Khoury, Matt Garland:
I-Vectors for speech activity detection. 334-339 - Themos Stafylakis, Patrick Kenny, Vishwa Gupta, Jahangir Alam, Marcel Kockmann:
Compensation for phonetic nuisance variability in speaker recognition using DNNs. 340-345 - Waad Ben Kheder, Driss Matrouf, Moez Ajili, Jean-François Bonastre:
Local binary patterns as features for speaker recognition. 346-351 - Alicia Lozano-Diez, Anna Silnova, Pavel Matejka, Ondrej Glembek, Oldrich Plchot, Jan Pesán
Analysis and Optimization of Bottleneck Features for Speaker Recognition. 352-357 - Andreas Nautsch
Robustness of Quality-based Score Calibration of Speaker Recognition Systems with respect to low-SNR and short-duration conditions. 358-365 - Pooyan Safari, Omid Ghahabi, Javier Hernando:
From Features to Speaker Vectors by means of Restricted Boltzmann Machine Adaptation. 366-371 - Yosef A. Solewicz, Hagai Aronowitz, Timo Becker:
Reducing Noise Bias in the i-Vector Space for Speaker Recognition. 372-376
Speaker Clustering and Diarization
- Giovanni Soldi, Massimiliano Todisco
Semi-supervised On-line Speaker Diarization for Meeting Data with Incremental Maximum A-posteriori Adaptation. 377-384 - Beatriz Martínez-González, José M. Pardo, Rubén San Segundo, Juan Manuel Montero-Martínez
Influence of transition cost in the segmentation stage of speaker diarization. 385-392 - Jesús Jorrín-Prieto, Carlos Vaquero
Analysis of the Impact of the Audio Database Characteristics in the Accuracy of a Speaker Clustering System. 393-399 - Abraham Woubie Zewoudie, Jordi Luque
Short- and Long-Term Speech Features for Hybrid HMM-i-Vector based Speaker Diarization System. 400-406 - Itay Salmun, Irit Opher, Itshak Lapidot:
On the Use of PLDA i-vector Scoring for Clustering Short Segments. 407-414
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