26 citations · 85 across the 14 of their papers we have counts for
10 papers · 1 filter
Maestro-U: Leveraging joint speech-text representation learning for zero supervised speech ASR
Zhehuai Chen, Ankur Bapna, Andrew Rosenberg +4
Training state-of-the-art Automated Speech Recognition (ASR) models typically requires a substantial amount of transcribed speech. In this work, we demonstrate that a modality-matc…
Analysis of Self-Attention Head Diversity for Conformer-based Automatic Speech Recognition
Kartik Audhkhasi, Yinghui Huang, Bhuvana Ramabhadran +1
Attention layers are an integral part of modern end-to-end automatic speech recognition systems, for instance as part of the Transformer or Conformer architecture. Attention is typ…
Injecting Text in Self-Supervised Speech Pretraining
Zhehuai Chen, Yu Zhang, Andrew Rosenberg +3
Self-supervised pretraining for Automated Speech Recognition (ASR) has shown varied degrees of success. In this paper, we propose to jointly learn representations during pretrainin…
Speech Recognition with Augmented Synthesized Speech
Andrew Rosenberg, Yu Zhang, Bhuvana Ramabhadran +4
Recent success of the Tacotron speech synthesis architecture and its variants in producing natural sounding multi-speaker synthesized speech has raised the exciting possibility of…
Learning to Speak Fluently in a Foreign Language: Multilingual Speech Synthesis and Cross-Language Voice Cloning
Yu Zhang, Ron J. Weiss, Heiga Zen +6
We present a multispeaker, multilingual text-to-speech (TTS) synthesis model based on Tacotron that is able to produce high quality speech in multiple languages. Moreover, the mode…
Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition
Xuesong Yang, Kartik Audhkhasi, Andrew Rosenberg +3
The performance of automatic speech recognition systems degrades with increasing mismatch between the training and testing scenarios. Differences in speaker accents are a significa…