74 citations · 104 across the 25 of their papers we have counts for
5 papers · 2 filters
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling
Jaejin Cho, Murali Karthick Baskar, Ruizhi Li +6
Sequence-to-sequence (seq2seq) approach for low-resource ASR is a relatively new direction in speech research. The approach benefits by performing model training without using lexi…
Low-Resource Contextual Topic Identification on Speech
Chunxi Liu, Matthew Wiesner, Shinji Watanabe +4
In topic identification (topic ID) on real-world unstructured audio, an audio instance of variable topic shifts is first broken into sequential segments, and each segment is indepe…
ESPnet: End-to-End Speech Processing Toolkit
Shinji Watanabe, Takaaki Hori, Shigeki Karita +9
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 w…
Multi-Modal Data Augmentation for End-to-End ASR
Adithya Renduchintala, Shuoyang Ding, Matthew Wiesner +1
We present a new end-to-end architecture for automatic speech recognition (ASR) that can be trained using \emph{symbolic} input in addition to the traditional acoustic input. This…
Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages
Matthew Wiesner, Chunxi Liu, Lucas Ondel +6
Automatic speech recognition (ASR) systems often need to be developed for extremely low-resource languages to serve end-uses such as audio content categorization and search. While…