Table of Contents

• Keynote: Pascal Belin [doi]
• Spoofing [doi]
• Text-dependent speaker recognition [doi]
• Keynote: Els Kindt [doi]
• Speaker recognition II [doi]
• Keynote: Simon King [doi]
• A Vocal Brain: Cerebral Processing of Voice InformationPascal Belin. [doi]
• Speaking naturally? It depends who is listeningSimoin King. [doi]
• Language Recognition [doi]
• Speaker Recognition I [doi]
• Voice conversion and spoofing [doi]
• Speaker diarization [doi]
• Speaker identification and Data protectionEls Kindt. [doi]
• Voice conversion [doi]
• Noise Robustness [doi]
• Impact of rhythm on forensic voice comparison reliabilityMoez Ajili, Solange Rossato, Dan Zhang, Jean-François Bonastre. 1-8 [doi]
• Segmental Content Effects on Text-dependent Automatic Accent RecognitionGeorgina Brown. 9-15 [doi]
• Homomorphic Encryption for Speaker Recognition: Protection of Biometric Templates and Vendor Model ParametersAndreas Nautsch, Sergey Isadskiy, Jascha Kolberg, Marta Gomez-Barrero, Christoph Busch. 16-23 [doi]
• Weakly Supervised Training of Speaker Identification ModelsMartin Karu, Tanel Alumäe. 24-30 [doi]
• The LEAP Language Recognition System for LRE 2017 Challenge - Improvements and Error AnalysisBharat Padi, Shreyas Ramoji, Vaishnavi Yeruva, Satish Kumar, Sriram Ganapathy. 31-38 [doi]
• Analysis of DNN-based Embeddings for Language Recognition on the NIST LRE 2017Alicia Lozano-Diez, Oldrich Plchot, Pavel Matejka, Ondrej Novotný, Joaquin Gonzalez-Rodriguez. 39-46 [doi]
• Analysis of BUT-PT Submission for NIST LRE 2017Oldrich Plchot, Pavel Matejka, Ondrej Novotný, Sandro Cumani, Alicia Lozano-Diez, Josef Slavícek, Mireia Díez, Frantisek Grézl, Ondrej Glembek, Mounika Kamsali, Anna Silnova, Lukás Burget, Lucas Ondel, Santosh Kesiraju, Johan Rohdin. 47-53 [doi]
• The MIT Lincoln Laboratory / JHU / EPITA-LSE LRE17 SystemFred Richardson, Pedro A. Torres-Carrasquillo, Jonas Borgstrom, Douglas E. Sturim, Youngjune Gwon, Jesús Villalba, Jan Trmal, Nanxin Chen, Réda Dehak, Najim Dehak. 54-59 [doi]
• Staircase Network: structural language identification via hierarchical attentive unitsTrung Ngo Trong, Ville Hautamäki, Kristiina Jokinen. 60-67 [doi]
• Language Recognition for Telephone and Video Speech: The JHU HLTCOE Submission for NIST LRE17Alan McCree, David Snyder, Gregory Sell, Daniel Garcia-Romero. 68-73 [doi]
• Exploring the Encoding Layer and Loss Function in End-to-End Speaker and Language Recognition SystemWeicheng Cai, Jinkun Chen, Ming Li. 74-81 [doi]
• The 2017 NIST Language Recognition EvaluationSeyed Omid Sadjadi, Timothée Kheyrkhah, Audrey Tong, Craig S. Greenberg, Douglas A. Reynolds, Elliot Singer, Lisa P. Mason, Jaime Hernandez-Cordero. 82-89 [doi]
• Approaches to Multi-domain Language RecognitionMitchell McLaren, Mahesh Kumar Nandwana, Diego Castán, Luciana Ferrer. 90-97 [doi]
• Convolutional Neural Network and Language Embeddings for End-to-End Dialect RecognitionSuwon Shon, Ahmed Ali, James Glass. 98-104 [doi]
• Spoken Language Recognition using X-vectorsDavid Snyder, Daniel Garcia-Romero, Alan McCree, Gregory Sell, Daniel Povey, Sanjeev Khudanpur. 105-111 [doi]
• End-to-End versus Embedding Neural Networks for Language Recognition in Mismatched ConditionsJesús Antonio Villalba López, Niko Brummer, Najim Dehak. 112-119 [doi]
• Incremental On-Line Clustering of Speakers' Short SegmentsRuth Aloni-Lavi, Irit Opher, Itshak Lapidot. 120-127 [doi]
• Latent Class Model for Single Channel Speaker DiarizationLiang He 0003, Xianhong Chen, Can Xu, Jia Liu. 128-133 [doi]
• VB-HMM Speaker Diarization with Enhanced and Refined Segment RepresentationXianhong Chen, Liang He, Can Xu, Yi Liu, Tianyu Liang, Jia Liu. 134-139 [doi]
• Low-latency speaker spotting with online diarization and detectionJose Patino, Ruiqing Yin, Héctor Delgado, Hervé Bredin, Alain Komaty, Guillaume Wisniewski, Claude Barras, Nicholas W. D. Evans, Sébastien Marcel. 140-146 [doi]
• Speaker Diarization based on Bayesian HMM with Eigenvoice PriorsMireia Díez, Lukás Burget, Pavel Matejka. 147-154 [doi]
• Domain-invariant I-vector Feature Extraction for PLDA Speaker VerificationMd. Hafizur Rahman, Ivan Himawan, David Dean, Clinton Fookes, Sridha Sridharan. 155-161 [doi]
• Reducing Domain Mismatch by Maximum Mean Discrepancy Based AutoencodersWei-Wei Lin, Man-Wai Mak, Longxin Li, Jen-Tzung Chien. 162-167 [doi]
• On the use of X-vectors for Robust Speaker RecognitionOndrej Novotný, Oldrich Plchot, Pavel Matejka, Ladislav Mosner, Ondrej Glembek. 168-175 [doi]
• Speaker Verification in Mismatched Conditions with Frustratingly Easy Domain AdaptationMd. Jahangir Alam, Gautam Bhattacharya, Patrick Kenny. 176-180 [doi]
• An Analysis of Transfer Learning for Domain Mismatched Text-independent Speaker VerificationChunlei Zhang, Shivesh Ranjan, John H. L. Hansen. 181-186 [doi]
• A Spoofing Benchmark for the 2018 Voice Conversion Challenge: Leveraging from Spoofing Countermeasures for Speech Artifact AssessmentTomi Kinnunen, Jaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda, Daisuke Saito, Fernando Villavicencio, Zhen-Hua Ling. 187-194 [doi]
• The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel MethodsJaime Lorenzo-Trueba, Junichi Yamagishi, Tomoki Toda, Daisuke Saito, Fernando Villavicencio, Tomi Kinnunen, Zhen-Hua Ling. 195-202 [doi]
• sprocket: Open-Source Voice Conversion SoftwareKazuhiro Kobayashi, Tomoki Toda. 203-210 [doi]
• The NU Non-Parallel Voice Conversion System for the Voice Conversion Challenge 2018Yi-Chiao Wu, Patrick Lumban Tobing, Tomoki Hayashi, Kazuhiro Kobayashi, Tomoki Toda. 211-218 [doi]
• NU Voice Conversion System for the Voice Conversion Challenge 2018Patrick Lumban Tobing, Yi-Chiao Wu, Tomoki Hayashi, Kazuhiro Kobayashi, Tomoki Toda. 219-226 [doi]
• Average Modeling Approach to Voice Conversion with Non-Parallel DataXiaohai Tian, Junchao Wang, Haihua Xu, Eng Siong Chng, Haizhou Li 0001. 227-232 [doi]
• Voice liveness detection using phoneme-based pop-noise detector for speaker verificationShihono Mochizuki, Sayaka Shiota, Hitoshi Kiya. 233-239 [doi]
• Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found dataJaime Lorenzo-Trueba, Fuming Fang, Xin Wang 0037, Isao Echizen, Junichi Yamagishi, Tomi Kinnunen. 240-247 [doi]
• The HCCL-CUHK System for the Voice Conversion Challenge 2018Songxiang Liu, Lifa Sun, Xixin Wu, Xunying Liu, Helen Meng. 248-254 [doi]
• Convolutional Neural Network Based Speaker De-IdentificationFahimeh Bahmaninezhad, Chunlei Zhang, John H. L. Hansen. 255-260 [doi]
• Bidirectional Voice Conversion Based on Joint Training Using Gaussian-Gaussian Deep Relational ModelKentaro Sone, Shinji Takaki, Toru Nakashika. 261-266 [doi]
• Phonetically Aware Exemplar-Based Prosody TransformationBerrak Sisman, Grandee Lee, Haizhou Li 0001. 267-274 [doi]
• A Regression Model of Recurrent Deep Neural Networks for Noise Robust Estimation of the Fundamental Frequency Contour of SpeechAkihiro Kato, Tomi Kinnunen. 275-282 [doi]
• BUT/Phonexia Bottleneck Feature ExtractorAnna Silnova, Pavel Matejka, Ondrej Glembek, Oldrich Plchot, Ondrej Novotný, Frantisek Grézl, Petr Schwarz, Lukás Burget, Jan Cernocký. 283-287 [doi]
• Evans, Laurent Pilati: An end-to-end spoofing countermeasure for automatic speaker verification using evolving recurrent neural networksGiacomo Valenti, Héctor Delgado, Massimiliano Todisco, Nicholas W. D. 288-295 [doi]
• Evans, Tomi Kinnunen, Kong-Aik Lee, Junichi Yamagishi: ASVspoof 2017 Version 2.0: meta-data analysis and baseline enhancementsHéctor Delgado, Massimiliano Todisco, Md. Sahidullah, Nicholas W. D. 296-303 [doi]
• An Audio Fingerprinting Approach to Replay Attack Detection on ASVSPOOF 2017 Challenge DataJoaquin Gonzalez-Rodriguez, Álvaro Escudero, Diego de Benito-Gorrón, Beltran Labrador, Javier Franco-Pedroso. 304-311 [doi]
• t-DCF: a Detection Cost Function for the Tandem Assessment of Spoofing Countermeasures and Automatic Speaker VerificationTomi Kinnunen, Kong-Aik Lee, Héctor Delgado, Nicholas W. D. Evans, Massimiliano Todisco, Md. Sahidullah, Junichi Yamagishi, Douglas A. Reynolds. 312-319 [doi]
• Perceptual Evaluation of the Effectiveness of Voice Disguise by Age ModificationRosa González Hautamäki, Anssi Kanervisto, Ville Hautamaki, Tomi Kinnunen. 320-326 [doi]
• How to train your speaker embeddings extractorMitchell McLaren, Diego Castán, Mahesh Kumar Nandwana, Luciana Ferrer, Emre Yilmaz. 327-334 [doi]
• End-to-end automatic speaker verification with evolving recurrent neural networksGiacomo Valenti, Adrien Daniel, Nicholas W. D. Evans. 335-341 [doi]
• Adversarial Learning and Augmentation for Speaker RecognitionJen-Tzung Chien, Kang-Ting Peng. 342-348 [doi]
• Gaussian meta-embeddings for efficient scoring of a heavy-tailed PLDA modelNiko Brummer, Anna Silnova, Lukás Burget, Themos Stafylakis. 349-356 [doi]
• Supervector Compression Strategies to Speed up I-Vector System DevelopmentVille Vestman, Tomi Kinnunen. 357-364 [doi]
• A Double Joint Bayesian Approach for J-Vector Based Text-dependent Speaker VerificationZiqiang Shi, Mengjiao Wang, Liu Liu, Huibin Lin, Rujie Liu. 365-371 [doi]
• Spoken Pass-Phrase Verification in the i-vector SpaceHossein Zeinali, Lukás Burget, Hossein Sameti, Honza Cernocký. 372-377 [doi]
• On deep speaker embeddings for text-independent speaker recognitionSergey Novoselov, Andrey Shulipa, Ivan Kremnev, Alexandr Kozlov, Vadim Shchemelinin. 378-385 [doi]
• DeepMine Speech Processing Database: Text-Dependent and Independent Speaker Verification and Speech Recognition in Persian and EnglishHossein Zeinali, Hossein Sameti, Themos Stafylakis. 386-392 [doi]
• Boosting the Performance of Spoofing Detection Systems on Replay Attacks Using q-Logarithm Domain Feature NormalizationMd. Jahangir Alam, Gautam Bhattacharya, Patrick Kenny. 393-398 [doi]