22 citations · 47 across the 9 of their papers we have counts for
9 papers
Zero-shot Cross-lingual Voice Transfer for TTS
Fadi Biadsy, Youzheng Chen, Isaac Elias +4
In this paper, we introduce a zero-shot Voice Transfer (VT) module that can be seamlessly integrated into a multi-lingual Text-to-speech (TTS) system to transfer an individual's vo…
Hierarchical Recurrent Adapters for Efficient Multi-Task Adaptation of Large Speech Models
Tsendsuren Munkhdalai, Youzheng Chen, Khe Chai Sim +3
Parameter efficient adaptation methods have become a key mechanism to train large pre-trained models for downstream tasks. However, their per-task parameter overhead is considered…
Streaming Parrotron for on-device speech-to-speech conversion
Oleg Rybakov, Fadi Biadsy, Xia Zhang +3
We present a fully on-device streaming Speech2Speech conversion model that normalizes a given input speech directly to synthesized output speech. Deploying such a model on mobile d…
Non-Parallel Voice Conversion for ASR Augmentation
Gary Wang, Andrew Rosenberg, Bhuvana Ramabhadran +4
Automatic speech recognition (ASR) needs to be robust to speaker differences. Voice Conversion (VC) modifies speaker characteristics of input speech. This is an attractive feature…
A Scalable Model Specialization Framework for Training and Inference using Submodels and its Application to Speech Model Personalization
Fadi Biadsy, Youzheng Chen, Xia Zhang +3
Model fine-tuning and adaptation have become a common approach for model specialization for downstream tasks or domains. Fine-tuning the entire model or a subset of the parameters…
Real time spectrogram inversion on mobile phone
Oleg Rybakov, Marco Tagliasacchi, Yunpeng Li +3
We present two methods of real time magnitude spectrogram inversion: streaming Griffin Lim(GL) and streaming MelGAN. We demonstrate the impact of looking ahead on perceptual qualit…
Residual Adapters for Parameter-Efficient ASR Adaptation to Atypical and Accented Speech
Katrin Tomanek, Vicky Zayats, Dirk Padfield +2
Automatic Speech Recognition (ASR) systems are often optimized to work best for speakers with canonical speech patterns. Unfortunately, these systems perform poorly when tested on…
Direct speech-to-speech translation with a sequence-to-sequence model
Ye Jia, Ron J. Weiss, Fadi Biadsy +4
We present an attention-based sequence-to-sequence neural network which can directly translate speech from one language into speech in another language, without relying on an inter…
Parrotron: An End-to-End Speech-to-Speech Conversion Model and its Applications to Hearing-Impaired Speech and Speech Separation
Fadi Biadsy, Ron J. Weiss, Pedro J. Moreno +2
We describe Parrotron, an end-to-end-trained speech-to-speech conversion model that maps an input spectrogram directly to another spectrogram, without utilizing any intermediate di…