Automatic Heteronym Resolution Pipeline Using RAD-TTS Aligners

no code implementations • 28 Feb 2023 • Jocelyn Huang, Evelina Bakhturina, Oktai Tatanov

Grapheme-to-phoneme (G2P) transduction is part of the standard text-to-speech (TTS) pipeline.

ACE-VC: Adaptive and Controllable Voice Conversion using Explicitly Disentangled Self-supervised Speech Representations

no code implementations • 16 Feb 2023 • Shehzeen Hussain, Paarth Neekhara, Jocelyn Huang, Jason Li, Boris Ginsburg

In this work, we propose a zero-shot voice conversion method using speech representations trained with self-supervised learning.

Self-Supervised Learning Speaker Verification +1

BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence

1 code implementation • 12 Jul 2022 • Isha Hameed, Samuel Sharpe, Daniel Barcklow, Justin Au-Yeung, Sahil Verma, Jocelyn Huang, Brian Barr, C. Bayan Bruss

By perturbing the input variables in rank order of importance, the goal is to assess the sensitivity of the model's performance.

Explainable artificial intelligence Explainable Artificial Intelligence (XAI)

QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions

15 code implementations • 22 Oct 2019 • Samuel Kriman, Stanislav Beliaev, Boris Ginsburg, Jocelyn Huang, Oleksii Kuchaiev, Vitaly Lavrukhin, Ryan Leary, Jason Li, Yang Zhang

We propose a new end-to-end neural acoustic model for automatic speech recognition.

Speech Recognition Audio and Speech Processing

NeMo: a toolkit for building AI applications using Neural Modules

1 code implementation • 14 Sep 2019 • Oleksii Kuchaiev, Jason Li, Huyen Nguyen, Oleksii Hrinchuk, Ryan Leary, Boris Ginsburg, Samuel Kriman, Stanislav Beliaev, Vitaly Lavrukhin, Jack Cook, Patrice Castonguay, Mariya Popova, Jocelyn Huang, Jonathan M. Cohen

NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI applications through re-usability, abstraction, and composition.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1