164 citations · 188 across the 12 of their papers we have counts for
13 papers
Building Synthetic Speaker Profiles in Text-to-Speech Systems
Jie Pu, Yixiong Meng, Oguz Elibol
The diversity of speaker profiles in multi-speaker TTS systems is a crucial aspect of its performance, as it measures how many different speaker profiles TTS systems could possibly…
Fusion of Embeddings Networks for Robust Combination of Text Dependent and Independent Speaker Recognition
Ruirui Li, Chelsea J. -T. Ju, Zeya Chen +3
By implicitly recognizing a user based on his/her speech input, speaker identification enables many downstream applications, such as personalized system behavior and expedited shop…
Scaling Laws for Acoustic Models
Jasha Droppo, Oguz Elibol
There is a recent trend in machine learning to increase model quality by growing models to sizes previously thought to be unreasonable. Recent work has shown that autoregressive ge…
Non-local convolutional neural networks (nlcnn) for speaker recognition
Haici Yang, Hongda Mao, Ruirui Li +2
Speaker recognition is the process of identifying a speaker based on the voice. The technology has attracted more attention with the recent increase in popularity of smart voice as…
Untangling in Invariant Speech Recognition
Cory Stephenson, Jenelle Feather, Suchismita Padhy +4
Encouraged by the success of deep neural networks on a variety of visual tasks, much theoretical and experimental work has been aimed at understanding and interpreting how vision n…
Shifted and Squeezed 8-bit Floating Point format for Low-Precision Training of Deep Neural Networks
Léopold Cambier, Anahita Bhiwandiwalla, Ting Gong +3
Training with larger number of parameters while keeping fast iterations is an increasingly adopted strategy and trend for developing better performing Deep Neural Network (DNN) mod…
Semi-supervised voice conversion with amortized variational inference
Cory Stephenson, Gokce Keskin, Anil Thomas +1
In this work we introduce a semi-supervised approach to the voice conversion problem, in which speech from a source speaker is converted into speech of a target speaker. The propos…
Measuring the Effectiveness of Voice Conversion on Speaker Identification and Automatic Speech Recognition Systems
Gokce Keskin, Tyler Lee, Cory Stephenson +1
This paper evaluates the effectiveness of a Cycle-GAN based voice converter (VC) on four speaker identification (SID) systems and an automated speech recognition (ASR) system for v…
Semi-supervised and Population Based Training for Voice Commands Recognition
Oguz H. Elibol, Gokce Keskin, Anil Thomas
We present a rapid design methodology that combines automated hyper-parameter tuning with semi-supervised training to build highly accurate and robust models for voice commands cla…
Adversarially Trained Autoencoders for Parallel-Data-Free Voice Conversion
Orhan Ocal, Oguz H. Elibol, Gokce Keskin +3
We present a method for converting the voices between a set of speakers. Our method is based on training multiple autoencoder paths, where there is a single speaker-independent enc…
Many-to-Many Voice Conversion with Out-of-Dataset Speaker Support
Gokce Keskin, Tyler Lee, Cory Stephenson +1
We present a Cycle-GAN based many-to-many voice conversion method that can convert between speakers that are not in the training set. This property is enabled through speaker embed…
Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks
Urs Köster, Tristan J. Webb, Xin Wang +11
Deep neural networks are commonly developed and trained in 32-bit floating point format. Significant gains in performance and energy efficiency could be realized by training and in…
Distributed Processing of Biosignal-Database for Emotion Recognition with Mahout
Varvara Kollia, Oguz H. Elibol
This paper investigates the use of distributed processing on the problem of emotion recognition from physiological sensors using a popular machine learning library on distributed m…