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