Poster Session Speech: source separation, enhancement, recognition, synthesis
in
Workshop: Machine Learning for Audio Signal Processing (ML4Audio)
Abstract
Poster abstracts and full papers: http://media.aau.dk/smc/ml4audio/
SPEECH SOURCE SEPARATION *Lijiang Guo and Minje Kim. Bitwise Source Separation on Hashed Spectra: An Efficient Posterior Estimation Scheme Using Partial Rank Order Metrics *Minje Kim and Paris Smaragdis. Bitwise Neural Networks for Efficient SingleChannel Source Separation *Mohit Dubey, Garrett Kenyon, Nils Carlson and Austin Thresher. Does Phase Matter For Monaural Source Separation?
SPEECH ENHANCEMENT *Rasool Fakoor, Xiaodong He, Ivan Tashev and Shuayb Zarar. Reinforcement Learning To Adapt Speech Enhancement to Instantaneous Input Signal Quality *Jong Hwan Ko, Josh Fromm, Matthai Phillipose, Ivan Tashev and Shuayb Zarar. Precision Scaling of Neural Networks for Efficient Audio Processing
AUTOMATIC SPEECH RECOGNITION Marius Paraschiv, Lasse Borgholt, Tycho Tax, Marco Singh and Lars Maaløe. Exploiting Nontrivial Connectivity for Automatic Speech Recognition *Brian Mcmahan and Delip Rao. Listening to the World Improves Speech Command Recognition * Andros Tjandra, Sakriani Sakti and Satoshi Nakamura. End-to-End Speech Recognition with Local Monotonic Attention Sri Harsha Dumpala, Rupayan Chakraborty and Sunil Kumar Kopparapu. A Novel Approach for Effective Learning in Low Resourced Scenarios
SPEECH SYNTHESIS *Yuxuan Wang, Rj SkerryRyan, Ying Xiao, Daisy Stanton, Joel Shor, Eric Battenberg, Rob Clark and Rif A. Saurous. Uncovering Latent Style Factors for Expressive Speech Synthesis *Younggun Lee, Azam Rabiee and Soo-Young Lee. Emotional End-to-End Neural Speech Synthesizer