activity
20202023
most citedOn End-to-end Multi-channel Time Domain Speech Separation in Reverberant Environments

49 citations · 66 across the 5 of their papers we have counts for

collaborators

5 papers

eess.AS2023

On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer

Md Asif Jalal, Pablo Peso Parada, Jisi Zhang +5

Smart devices serviced by large-scale AI models necessitates user data transfer to the cloud for inference. For speech applications, this means transferring private user informatio…

cs.SD2022★ 6 cited

On monoaural speech enhancement for automatic recognition of real noisy speech using mixture invariant training

Jisi Zhang, Catalin Zorila, Rama Doddipatla +1

In this paper, we explore an improved framework to train a monoaural neural enhancement model for robust speech recognition. The designed training framework extends the existing mi…

cs.SD2021★ 2 cited

Teacher-Student MixIT for Unsupervised and Semi-supervised Speech Separation

Jisi Zhang, Catalin Zorila, Rama Doddipatla +1

In this paper, we introduce a novel semi-supervised learning framework for end-to-end speech separation. The proposed method first uses mixtures of unseparated sources and the mixt…

eess.AS2021★ 9 cited

Time-Domain Speech Extraction with Spatial Information and Multi Speaker Conditioning Mechanism

Jisi Zhang, Catalin Zorila, Rama Doddipatla +1

In this paper, we present a novel multi-channel speech extraction system to simultaneously extract multiple clean individual sources from a mixture in noisy and reverberant environ…

eess.AS2020★ 49 cited

On End-to-end Multi-channel Time Domain Speech Separation in Reverberant Environments

Jisi Zhang, Catalin Zorila, Rama Doddipatla +1

This paper introduces a new method for multi-channel time domain speech separation in reverberant environments. A fully-convolutional neural network structure has been used to dire…