Tsubasa Ochiai

Probing Self-supervised Learning Models with Target Speech Extraction

2024 · arXiv (Cornell University)

Large-scale pre-trained self-supervised learning (SSL) models have shown remarkable advancements in speech-related tasks. However, the utilization of these models in complex multi-talker scenarios, such as extracting a target speaker in a mixture, is yet to …

Target Speech Extraction with Pre-Trained Self-Supervised Learning Models

2024

Pre-trained self-supervised learning (SSL) models have achieved remarkable success in various speech tasks. However, their potential in target speech extraction (TSE) has not been fully exploited. TSE aims to extract the speech of a target …

ESPnet: End-to-End Speech Processing Toolkit

2018 · arXiv (Cornell University)

This paper introduces a new open source platform for end-to-end speech processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts widely-used dynamic neural network toolkits, Chainer and PyTorch, as a …