Search Results for author:
Found 9 papers, 2 papers with code
SpeechComposer: Unifying Multiple Speech Tasks with Prompt Composition
Existing speech language models typically utilize task-dependent prompt tokens to unify various speech tasks in a single model.
Adapting Multi-Lingual ASR Models for Handling Multiple Talkers
State-of-the-art large-scale universal speech models (USMs) show a decent automatic speech recognition (ASR) performance across multiple domains and languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Target Sound Extraction with Variable Cross-modality Clues
Automatic target sound extraction (TSE) is a machine learning approach to mimic the human auditory perception capability of attending to a sound source of interest from a mixture of sources.
ESPnet-SE++: Speech Enhancement for Robust Speech Recognition, Translation, and Understanding
To showcase such integration, we performed experiments on carefully designed synthetic datasets for noisy-reverberant multi-channel ST and SLU tasks, which can be used as benchmark corpora for future research.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Towards Low-distortion Multi-channel Speech Enhancement: The ESPNet-SE Submission to The L3DAS22 Challenge
This paper describes our submission to the L3DAS22 Challenge Task 1, which consists of speech enhancement with 3D Ambisonic microphones.
SkiM: Skipping Memory LSTM for Low-Latency Real-Time Continuous Speech Separation
We adopt the time-domain speech separation method and the recently proposed Graph-PIT to build a super low-latency online speech separation model, which is very important for the real application.
Closing the Gap Between Time-Domain Multi-Channel Speech Enhancement on Real and Simulation Conditions
The deep learning based time-domain models, e. g. Conv-TasNet, have shown great potential in both single-channel and multi-channel speech enhancement.
Dual-Path Modeling for Long Recording Speech Separation in Meetings
A transformer-based dual-path system is proposed, which integrates transform layers for global modeling.
Continuous Speech Separation Using Speaker Inventory for Long Multi-talker Recording
Leveraging additional speaker information to facilitate speech separation has received increasing attention in recent years.
